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WO2023128113A1 - Serveur de gestion d'informations d'objet dangereux apte à estimer la taille réelle d'un objet dangereux sur une route conjointement avec un terminal de collecte d'informations monté sur un véhicule, et son procédé de fonctionnement - Google Patents

Serveur de gestion d'informations d'objet dangereux apte à estimer la taille réelle d'un objet dangereux sur une route conjointement avec un terminal de collecte d'informations monté sur un véhicule, et son procédé de fonctionnement Download PDF

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Publication number
WO2023128113A1
WO2023128113A1 PCT/KR2022/011715 KR2022011715W WO2023128113A1 WO 2023128113 A1 WO2023128113 A1 WO 2023128113A1 KR 2022011715 W KR2022011715 W KR 2022011715W WO 2023128113 A1 WO2023128113 A1 WO 2023128113A1
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WO
WIPO (PCT)
Prior art keywords
information
dangerous
image
size
candidate
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Ceased
Application number
PCT/KR2022/011715
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English (en)
Korean (ko)
Inventor
노재민
정만식
노엘리자베스김
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Dareesoft Inc
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Dareesoft Inc
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Publication date
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Publication of WO2023128113A1 publication Critical patent/WO2023128113A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
    • B60W40/06—Road conditions
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/40—Business processes related to the transportation industry
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/40—Image enhancement or restoration using histogram techniques
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/11—Region-based segmentation
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/60—Analysis of geometric attributes
    • G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/90—Determination of colour characteristics
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/16—Anti-collision systems

Definitions

  • the present invention relates to a dangerous substance information management server capable of estimating the actual size of a dangerous object on a road through interworking with an information collection terminal mounted in a vehicle, and an operation method thereof.
  • the present invention proposes a dangerous substance information management server capable of estimating the actual size of dangerous substances on the road through interworking with an information collection terminal mounted on a vehicle and an operation method thereof, thereby obtaining and managing more accurate information about dangerous substances on the road. We want to help you do it.
  • a dangerous material information management server capable of estimating the actual size of a dangerous material on a road through interworking with an information collection terminal mounted on a vehicle includes a plurality of vehicles pre-designated to collect dangerous material information on the road.
  • a camera capable of photographing the front of each vehicle in order to collect dangerous material information on the road has a first preset focal length and a preset first size image ( It is a camera configured so that the image) is formed on the image sensor), a distance measurement sensor for measuring the separation distance to a dangerous object in front of each vehicle, and a GPS (Global Positioning System) that can collect location information of each vehicle.
  • GPS Global Positioning System
  • An information collection terminal is mounted - Dangerous substance information collected by -
  • Each of the dangerous substance information is a photographic image of a dangerous substance on the road photographed through an information collection terminal mounted in a vehicle and a location where the photographed image was photographed. It is composed of location information and size information about dangerous substances - is stored in the dangerous substance information database, from a first information collection terminal mounted on a first vehicle, which is any one of the plurality of vehicles, to the first information collection terminal.
  • the first location information of the point where the first captured image is captured obtained through the GPS provided in the information collection terminal, is received, based on the first focal length and the first separation distance, the first dangerous object
  • a size information generation unit for generating the estimated actual size of the first dangerous object as first size information about the first dangerous object, and when the first size information is generated, the first captured image
  • a dangerous substance information storage processor configured to generate first dangerous substance information composed of the first location information and the first size information and then store the first dangerous substance information in the dangerous substance information database.
  • a method of operating a dangerous substance information management server capable of estimating the actual size of a dangerous substance on a road through interworking with an information collection terminal mounted on a vehicle is a method of collecting dangerous substance information on a road in advance.
  • Designated plurality of vehicles Each of the plurality of vehicles has a camera capable of photographing the front of each vehicle in order to collect dangerous material information on the road (the camera has a first preset focal length and a preset first focal length).
  • a camera configured so that an image of the size of 1 is formed on the image sensor), a distance measuring sensor for measuring the separation distance to a dangerous object in front of each vehicle, and an information collection terminal equipped with a GPS capable of collecting location information of each vehicle Mounted - Hazardous material information collected by -
  • Each of the dangerous material information includes a photographed image of a dangerous material on the road captured through an information collection terminal mounted in a vehicle, location information of a point where the photographed image was captured, and dangerous material Consisting of size information for - Maintaining the stored dangerous goods information database, from a first information collection terminal mounted on a first vehicle that is any one of the plurality of vehicles, to the first information collection terminal A first photographed image of a first dangerous substance photographed through a camera provided thereto, a first separation distance between the first vehicle and the first dangerous substance measured through a distance measurement sensor provided in the first information collection terminal, and the first 1
  • the first location information of the point where the first captured image is captured obtained through the GPS provided in the information collection terminal, is received, based on the
  • the present invention proposes a dangerous substance information management server capable of estimating the actual size of dangerous substances on the road through interworking with an information collection terminal mounted on a vehicle and an operation method thereof, thereby obtaining and managing more accurate information about dangerous substances on the road. can support you to do it.
  • FIG. 1 is a diagram showing the structure of a dangerous substance information management server capable of estimating the actual size of a dangerous object on a road through interworking with an information collection terminal mounted on a vehicle according to an embodiment of the present invention.
  • FIGS. 2 to 4 are diagrams for explaining the operation of a dangerous substance information management server capable of estimating the actual size of a dangerous object on a road through interworking with an information collection terminal mounted on a vehicle according to an embodiment of the present invention.
  • FIG. 5 is a flowchart illustrating an operating method of a dangerous substance information management server capable of estimating the actual size of a dangerous object on a road through interworking with an information collection terminal mounted on a vehicle according to an embodiment of the present invention.
  • each component, functional block, or means may be composed of one or more sub-components, and the electrical, electronic, and mechanical functions performed by each component are electronic It may be implemented with various known elements or mechanical elements such as circuits, integrated circuits, ASICs (Application Specific Integrated Circuits), and may be implemented separately or two or more may be integrated into one.
  • ASICs Application Specific Integrated Circuits
  • the blocks of the accompanying block diagram or the steps of the flowchart are computer program instructions that perform designated functions by being loaded into a processor or memory of a device capable of data processing, such as a general-purpose computer, a special purpose computer, a portable notebook computer, and a network computer.
  • a device capable of data processing such as a general-purpose computer, a special purpose computer, a portable notebook computer, and a network computer.
  • these computer program instructions may be stored in a memory included in a computer device or in a computer readable memory
  • the functions described in blocks of a block diagram or steps of a flowchart are produced as a product containing instruction means for performing them. It could be.
  • each block or each step may represent a module, segment or portion of code that includes one or more executable instructions for executing specified logical function(s).
  • FIG. 1 is a diagram showing the structure of a dangerous substance information management server capable of estimating the actual size of a dangerous object on a road through interworking with an information collection terminal mounted on a vehicle according to an embodiment of the present invention.
  • a camera capable of photographing the front of each vehicle in order to collect dangerous material information on the road has a preset first focal length and a preset first size image ( It is a camera configured so that the image) is formed on the image sensor), a distance measurement sensor for measuring the separation distance to a dangerous object in front of each vehicle, and a GPS (Global Positioning System) that can collect location information of each vehicle.
  • An information collection terminal is installed.
  • the focal length means the distance between the lens of the camera and the focal plane where the light transmitted through the lens of the camera is converged in a horizontal state.
  • the information collection terminal analyzes an image captured through a camera while each vehicle is running based on the dangerous material detection model, It is possible to detect a dangerous object in front of the vehicle, and when a dangerous object is detected in front of each vehicle, the distance to the dangerous object is measured through a distance measurement sensor provided in the information collection terminal, and at the same time, the information collection terminal Location information of a point where dangerous goods are detected may be obtained through the provided GPS and transmitted to the dangerous goods information management server.
  • the dangerous goods information management server 110 includes a dangerous goods information database 111, a size information generation unit 112, and a dangerous goods information storage processing unit 113. do.
  • dangerous material information database 111 dangerous material information collected by a plurality of vehicles pre-designated to collect dangerous material information on the road (each of the dangerous material information is photographed through an information collection terminal mounted on the vehicle). Consisting of a photographed image, location information of a point where the photographed image was photographed, and size information of a dangerous object) are stored.
  • dangerous material information collected by a plurality of vehicles previously designated to collect dangerous material information on the road may be stored in the dangerous material information database 111 .
  • Dangerous goods information shooting image location information size information Dangerous Goods Information 1 shooting image 1 location information 1 size information 1 Dangerous goods information 2 shooting image 2 location information 2 size information 2 Dangerous Goods Information 3 shooting image 3 location information 3 size information 3 Dangerous Goods Information 4 shooting image 4 location information 4 size information 4 Dangerous Goods Information 5 shooting image 5 location information 5 size information 5
  • the size information generator 112 is configured from the first information collection terminal 150 mounted on the first vehicle 140, which is one of the plurality of vehicles, through a camera provided in the first information collection terminal 150.
  • the first dangerous substance is determined based on the first focal length and the first separation distance. After estimating the actual size of , the estimated actual size of the first dangerous object is generated as first size information for the first dangerous object.
  • the size information generator 112 is a specific configuration for generating the first size information for the first dangerous substance, the size adjustment unit 114, the vertical length check unit 115 ), an actual vertical length calculation unit 116, an area calculation unit 117, and a size information generation processing unit 118.
  • the size adjusting unit 114 adjusts the size of the first captured image to the first information collection terminal 150. It is adjusted to a size corresponding to the first size, which is the size of an image formed on an image sensor of a camera provided in the terminal 150.
  • the vertical length checking unit 115 generates a rectangular area surrounding the outer periphery of an object corresponding to the first dangerous object in the resized first captured image, and then the resized first captured image. Check the vertical length of the rectangular area in the image.
  • the camera provided in the first information collection terminal 150 'Shooting image 6' for the first dangerous object photographed through 'separation distance 1' between the first vehicle 140 and the first dangerous object measured through the distance measurement sensor provided in the first information collection terminal 150 And it is assumed that 'location information 6' of a point where the 'captured image 6' acquired through the GPS provided in the first information collecting terminal 150 is received.
  • the size adjusting unit 114 may adjust the size of the 'photographed image 6' to a size corresponding to the first size, which is the size of an image formed on an image sensor of a camera provided in the first information collection terminal 150.
  • the vertical length check unit 115 determines the first 1
  • a preset object detection model for extracting an object corresponding to a dangerous substance from a photographed image may be utilized.
  • the vertical length checking unit 115 utilizes a You Only Look Once (YOLO)-based object detection model to detect the object 211 corresponding to the first dangerous object in the resized 'photographed image 6 210'. ) can be extracted.
  • YOLO You Only Look Once
  • the vertical length checking unit 115 determines the resized 'captured image 6 210'. ', after creating a square area 212 surrounding the outer periphery of the object 211 corresponding to the first dangerous substance, the vertical length of the square area 212 in the resized 'photographed image 6 210'. (H, 213) can be confirmed.
  • the actual vertical length calculating unit 116 calculates the Calculate the actual vertical length of the rectangular area.
  • h denotes an actual vertical length of the quadrangular region
  • H denotes a vertical length of the quadrangular region in the resized first captured image
  • f denotes the first focal length
  • l denotes the first separation distance.
  • Equation 1 can be explained using FIG. 3 as follows.
  • the dangerous material information management server 110 receives 'captured image 6', 'separation distance 1', and 'location information 6' from the first information collection terminal 150, the vertical length Assume that the vertical length (H, 213) of the blind area 212 in the resized 'photographed image 6 (210)' is confirmed by the confirmation unit 115.
  • the angle formed by each of the upper ends 219 of the rectangular area 212 in the resized 'photographed image 6 210' is equal to ' ⁇ '.
  • Equation 2 Equation 1 for the actual vertical length (h, 214) of the blind area 212 can be derived.
  • the area calculating unit 117 calculates the area of the rectangular area in the resized first captured image.
  • the size information generation processing unit 118 determines the ratio between the vertical length of the square region in the resized first photographed image and the actual vertical length of the square region in the resized first photographed image. After estimating the actual size of the first dangerous object by calculating the real area of the blind spot from the area of the blind spot, the estimated real size of the first dangerous object is generated as the first size information.
  • the actual vertical length (h, 214) of the blind area 212 is calculated according to Equation 1 as in the above example.
  • the ratio between the vertical length (H, 213) of the blind area 212 in the resized 'photographed image 6 (210)' and the actual vertical length (h, 214) of the blind area 212 is '10 Let's assume '3 :1'.
  • the area calculating unit 117 may calculate the area of the rectangular area 212 in the resized 'photographed image 6 210' as 'A'.
  • the size information generation processing unit 118 determines the vertical length (H, 213) of the blind area 212 in the resized 'photographed image 6 (210)' and the actual vertical length (h) of the blind area 212. , 214), the actual area of the blind area 212 is calculated from the area A of the blind spot 212 in the resized 'photographed image 6 210' according to the ratio '10 3 : 1'.
  • the actual size of the first dangerous object can be estimated as '10 6 ⁇ A'.
  • the size information generation processing unit 118 may generate '10 6 ⁇ A', which is the estimated actual size of the first dangerous object, as 'size information 6', which is size information on the first dangerous object.
  • the dangerous substance information storage processing unit 113 stores the first image composed of the first captured image, the first location information, and the first size information. After generating the dangerous substance information, the first dangerous substance information is stored in the dangerous substance information database 111 .
  • '10 6 ⁇ A' the actual size of the first dangerous object
  • 'size information 6' which is the size information for the first dangerous object
  • the dangerous material information storage processing unit 113 generates 'dangerous material information 6', which is the first dangerous material information consisting of 'photographed image 6', 'position information 6', and 'size information 6', and then the following Table 2 and Likewise, 'dangerous material information 6' may be stored in the dangerous material information database 111 .
  • Dangerous goods information shooting image location information size information Dangerous Goods Information 1 shooting image 1 location information 1 size information 1 Dangerous goods information 2 shooting image 2 location information 2 size information 2 Dangerous Goods Information 3 shooting image 3 location information 3 size information 3 Dangerous Goods Information 4 shooting image 4 location information 4 size information 4 Dangerous Goods Information 5 shooting image 5 location information 5 size information 5 Dangerous Goods Information 6 shooting image 6 location information 6 size information 6
  • the dangerous material information management server 110 may further include a duplicate determination unit 119 and a dangerous material information deletion unit 120 .
  • the overlapping determination unit 119 determines, among the dangerous goods information stored in the dangerous goods information database 111, It is determined whether there is dangerous material information overlapping with the first dangerous material information.
  • the overlap determination unit 119 is a detailed configuration for determining whether or not there exists dangerous material information overlapping with the first dangerous material information among the dangerous material information stored in the dangerous material information database 111, and makes a first judgment. It may include a unit 121 , an image similarity calculation unit 122 and a second determination unit 123 .
  • the first determination unit 121 determines, among the dangerous substance information stored in the dangerous substance information database 111, Whether or not dangerous substance information including location information in which the separation distance from the first location information is within a preset standard distance and size information in which a difference from the first size information is within a preset standard size exists judge
  • the image similarity calculation unit 122 includes location information in which a separation distance from the first location information is within the reference distance among the dangerous substance information stored in the dangerous substance information database 111, and the first size information. If it is determined that at least one candidate dangerous material information exists as dangerous material information including size information having a difference between the size and the standard size, for each of the at least one candidate dangerous material information, a photograph is included in each candidate dangerous material information. An image similarity corresponding to each of the at least one candidate dangerous substance information is calculated by calculating an image similarity between an image and the first photographed image.
  • the image similarity calculation unit 122 is a specific configuration for calculating the image similarity corresponding to each of the at least one candidate dangerous substance information, and includes an image histogram calculation unit 124, a vector similarity calculation unit 125 and an image similarity calculation processing unit 126.
  • the image histogram calculation unit 124 includes positional information in which a separation distance from the first positional information is within the reference distance among the dangerous goods information stored in the dangerous goods information database 111, and at the same time, the first size If it is determined that the at least one candidate dangerous material information exists as dangerous material information including size information whose difference from the information is within the standard size, the at least one candidate dangerous material information includes a photographed image and the first dangerous material information. For each captured image, an image histogram for each color channel is calculated.
  • the image histogram means a graph in which the horizontal axis is the pixel value and the vertical axis is the number of pixels in order to represent the characteristics of the image, and according to the color mode of the image, RGB (Red, Green, Blue) , CMYK (Cyan, Magenta, Yellow, Black), etc. may be configured for each color channel.
  • RGB Red, Green, Blue
  • CMYK Cyan, Magenta, Yellow, Black
  • the vector similarity calculating unit 125 calculates an image histogram for each color channel for each of the first captured image and the captured image included in each of the at least one candidate dangerous substance information by the image histogram calculating unit 124, the at least one of the at least one candidate dangerous substance information.
  • a vector having as components the number of pixels for each pixel value included in the image histogram for the photographed image included in each candidate dangerous material information, for each color channel, and included in the image histogram for the first image By calculating the vector similarity between vectors having the number of pixels for each pixel value as a component, the vector similarity for each color channel for each of the at least one candidate dangerous substance information is calculated.
  • Equation 3 a cosine similarity according to Equation 3 below or a Euclidean distance according to Equation 4 below may be used.
  • Equation 1 S is the cosine similarity between vector A and vector B, and has a value between -1 and 1
  • a i denotes the i-th component of vector A
  • B i denotes the i-th component of vector B. do.
  • the greater the cosine similarity between two vectors the more similar the two vectors are to each other.
  • Equation 4 D is the Euclidean distance between vector A and vector B, A i denotes the i-th component of vector A, and B i denotes the i-th component of vector B.
  • a i denotes the i-th component of vector A
  • B i denotes the i-th component of vector B.
  • the image similarity calculation processing unit 126 calculates the vector similarity for each color channel for each of the at least one candidate dangerous substance information by the vector similarity calculation unit 125, and for each of the at least one candidate dangerous substance information, each candidate dangerous substance information Image similarity corresponding to each of the at least one candidate dangerous substance information is calculated by calculating an average value of vector similarities for each color channel as an image similarity between a captured image included in each candidate dangerous substance information and the first captured image. .
  • the preset reference distance is set to '10m', and the preset reference size is set to '5cm 2 '. Assume that 'dangerous goods information 6' is stored in 111).
  • the first determination unit 121 includes location information in which the separation distance from 'location information 6' is within '10m' among the dangerous material information stored in the dangerous material information database 111 as shown in Table 2 above. At the same time, it is possible to check whether dangerous substance information including size information having a difference from 'size information 6' within '5 cm 2 ' exists.
  • the first determination unit 121 selects 'location information 1, location information 2, location information 3, Location information 4, location information 5' and 'location information 6' are compared with each other, and 'location information 6' is obtained for each of 'location information 1, location information 2, location information 3, location information 4, and location information 5'. It is possible to check whether the separation distance is within '10m'.
  • the first determination unit 121 determines the size information included in each of the dangerous goods information stored in the dangerous goods information database 111 as shown in Table 2, 'size information 1, size information 2, size information 3, By comparing 'size information 4, size information 5' and 'size information 6' with each other, 'size information 1, size information 2, size information 3, size information 4, and size information 5', respectively, 'size information 6' It is possible to check whether the separation distance from the target is within '5cm 2 '.
  • the location information within '10m' of the distance from 'location information 6' is included, and at the same time, 'size information 6 Assume that it is confirmed that there is at least one candidate dangerous material information, 'dangerous material information 2, dangerous material information 5', as dangerous material information including size information within '5 cm 2 '.
  • the image histogram calculator 124 calculates the following As shown in Table 3, image histograms for each color channel for 'captured image 2 and 5' and 'captured image 6' can be calculated.
  • the vector similarity calculating unit 125 calculates a vector having as components the number of pixels for each pixel value included in the image histogram for each of the captured images, for each color channel, for each of 'photographed image 2 and captured image 5', and 'photographed image
  • the vector similarity for each color channel for 'dangerous material information 2 and dangerous material information 5' can be calculated.
  • a detailed process for the vector similarity calculation unit 125 to calculate the vector similarity for each color channel for 'dangerous material information 2' among 'dangerous material information 2 and dangerous material information 5' is as follows.
  • the image histogram for each color channel for 'captured image 2' is 'histogram 1, histogram 2, and histogram 3'
  • the image histogram for each color channel for 'captured image 6' is 'histogram 7'.
  • histogram 8 histogram 9' the vector similarity calculation unit 125 determines between the vector having the number of pixels for each pixel value included in 'histogram 1' and the vector having the number of pixels for each pixel value included in 'histogram 7' as a component. By calculating the vector similarity, it is possible to calculate the vector similarity (S 1 ) for the color channel R of 'dangerous goods information 2'.
  • the vector similarity calculation unit 125 calculates the vector similarity between the vector having the number of pixels per pixel value included in 'Histogram 2' as a component and the vector having the number of pixels for each pixel value included in 'Histogram 8' as a component.
  • a vector similarity (S 2 ) for color channel G of dangerous goods information 2' can be calculated.
  • the vector similarity calculation unit 125 calculates the vector similarity between the vector having the number of pixels for each pixel value included in 'Histogram 3' as a component and the vector having the number of pixels for each pixel value included in 'Histogram 9' as a component,
  • a vector similarity (S 3 ) for color channel B of 'dangerous goods information 2' may be calculated.
  • the vector similarity calculation unit 125 calculates the vector similarity between the histograms for each color channel called RGB, thereby calculating the vector similarity for each color channel for 'dangerous substance information 2' as 'S 1 , S 2 , S 3 '. there is.
  • the vector similarity calculation unit 125 may calculate the vector similarity for each color channel for 'dangerous material information 2 and dangerous material information 5' as shown in Table 4 below.
  • At least one Candidate Dangerous Goods Information Vector similarity by color channel R(Red) G(Green) B(Blue) Dangerous goods information 2 S1 S2 S3 Dangerous Goods Information 5 S4 S5 S6
  • the image similarity calculation processing unit 126 calculates an average value of vector similarities for each color channel for each candidate dangerous substance information for each of the at least one candidate dangerous substance information 'dangerous material information 2 and dangerous material information 5', each candidate dangerous material information It is possible to calculate image similarity corresponding to each of 'dangerous material information 2 and dangerous material information 5' by calculating the image similarity between 'captured image 2 and 5' and 'captured image 6', which are captured images included in .
  • the image similarity calculation unit 126 calculates 'S 1 , S 2 , ', which is the average value of S 3 ' ' may be calculated as image similarity between 'captured image 2' and 'captured image 6'.
  • the image similarity calculation processing unit 126 calculates the average value of 'S 4 , S 5 , S 6 '. ' may be calculated as image similarity between 'captured image 5' and 'captured image 6'.
  • the image similarity calculation processing unit 126 calculates the image similarity corresponding to each of 'dangerous material information 2 and dangerous material information 5', ' , ' can be calculated.
  • the dangerous goods information management server 110 is a method for calculating image similarity between photographed images, in addition to the method of calculating image similarity through comparison of image histograms as described above, A method of calculating image similarity between captured images using a pre-built artificial intelligence-based image similarity calculation model may be used. That is, the dangerous material information management server 110 calculates the image similarity between a captured image included in the at least one piece of dangerous material information and the first captured image by utilizing a predetermined artificial intelligence-based image similarity calculation model, An image similarity corresponding to each candidate dangerous substance information may be calculated.
  • the second determination unit 123 calculates the image similarity corresponding to each of the at least one candidate dangerous substance information, It is checked whether the similarity exceeds a preset criterion, and if it is confirmed that there is an image similarity exceeding the criterion similarity among the image similarities corresponding to each of the at least one candidate dangerous material information, the dangerous material information database 111 Among the stored dangerous material information, it is determined that there is dangerous material information overlapping with the first dangerous material information.
  • the preset standard similarity is set to '0.9', and as in the above-described example, images corresponding to each of the at least one candidate dangerous material information 'dangerous material information 2 and dangerous material information 5' by the image similarity calculation unit 122 similarity, ' , Assume that it is calculated as '.
  • the second determination unit 123 determines the degree of image similarity corresponding to 'dangerous material information 2 and dangerous material information 5' respectively. , It can be checked whether ' exceeds '0.9', which is the standard similarity.
  • the second determination unit 123 determines 'dangerous goods', which is the first dangerous goods information, among the dangerous goods information stored in the dangerous goods information database 111 as shown in Table 3 above. It can be determined that there is overlapping dangerous goods information with Information 6'.
  • the dangerous material information deletion unit deletes the first dangerous substance information stored in the dangerous substance information database 110 .
  • the dangerous material information deletion unit 120 may delete 'dangerous material information 6' stored in the dangerous material information database 110 as shown in Table 5 below.
  • Dangerous goods information shooting image location information size information Dangerous Goods Information 1 shooting image 1 location information 1 size information 1 Dangerous goods information 2 shooting image 2 location information 2 size information 2 Dangerous Goods Information 3 shooting image 3 location information 3 size information 3 Dangerous Goods Information 4 shooting image 4 location information 4 size information 4 Dangerous Goods Information 5 shooting image 5 location information 5 size information 5
  • the dangerous goods information management server 110 stores the dangerous goods information database 111 in the dangerous goods information database 111. By deleting the stored first dangerous substance information, it is possible to manage dangerous substance information stored in the dangerous substance information database 111 so that they do not overlap each other.
  • the dangerous goods information management server 110 provides the second dangerous goods information, which is any one of the dangerous goods information stored in the dangerous goods information database 111, from the manager terminal 160.
  • the second dangerous substance information is encrypted and transmitted to the manager terminal 160, and includes an encryption key storage unit 127, an image segmentation unit 128, a key image generator for restoration 129, A mapping matrix generator 130, a data set generator 131, a substitution matrix generator 132, an encryption image generator 133, and an image transmitter 134 may be further included.
  • An encryption key previously shared with the manager terminal 160 is stored in the encryption key storage unit 127 .
  • 'encryption key 1' may be stored in the encryption key storage unit 127.
  • the image segmentation unit 128 displays information from the dangerous substance information database 111.
  • the second dangerous substance information is extracted, and the second captured image included in the second dangerous substance information is divided into n ⁇ n partial regions consisting of n horizontally (n is a natural number equal to or greater than 2) and n vertically.
  • the key image generator 129 for restoration randomly selects k (k is a natural number greater than or equal to 2 and less than n 2 ) first partial regions among the nxn partial regions constituting the second captured image; For each of the first subregions, after randomly selecting an odd number of first pixels for each subregion, randomly changing a pixel value for each of the first pixels selected for each subregion; Among the n ⁇ n subregions, an even number of second pixels are randomly selected for each of the n 2 -k second subregions excluding the first subregions, and then each second pixel is selected at random.
  • a key image for restoration is generated by randomly changing a pixel value for each of the second pixels selected for each partial region.
  • the mapping matrix generator 130 assigns '1' to the same point as the first partial regions among the n x n partial regions.
  • An n x n mapping matrix composed of '0' and '1' is generated by allocating components and allocating components of '0' to the same points as the second subregions.
  • the data set generator 131 checks the second location information and the second size information included in the second dangerous substance information, and obtains the second location information. and a data set composed of the second size information.
  • the substitution matrix generation unit 132 divides the data set into k pieces to generate k pieces of split data, randomly generates n 2 -k pieces of dummy data, and then nxn elements constituting the mapping matrix Among them, the k pieces of split data are inserted one by one at the points where the components of '1' are located, and the n 2 -k pieces of dummy data are inserted one by one at the points where the components of '0' are located, thereby replacing nxn size. create a matrix
  • the encryption image generator 133 generates an encryption image by encrypting the second captured image with the encryption key.
  • the image transmission unit 134 transmits the encryption image, the substitution matrix, and the key image for restoration to the manager terminal 160 .
  • an image segmentation unit 128, a key image generation unit for restoration 129, a mapping matrix generation unit 130, a data set generation unit 131, a substitution matrix generation unit 132, an encryption image generation unit 133 ) and the operation of the image transmission unit 134 will be described in detail, for example.
  • the image dividing unit 128 extracts 'dangerous material information 3' from the dangerous material information database 111 as shown in Table 5, and converts 'photographed image 3' included in 'dangerous material information 3' into '3' horizontally and It can be divided into '3 x 3' subregions consisting of '3' vertically.
  • 'photographed image 3' is the same as the figure indicated by reference numeral 410 in FIG. It can be divided into '9' partial regions 411, 412, 413, 414, 415, 416, 417, 418, and 419.
  • the key image generator 129 for restoration randomly selects '4' first partial areas among '9' partial areas 411 , 412 , 413 , 414 , 415 , 416 , 417 , 418 , and 419 . can choose to
  • the key image generator 129 for restoration may randomly select an odd number of first pixels for each of the first partial regions 412 , 416 , 417 , and 419 . there is.
  • the key image generation unit 129 may randomly change a pixel value of each of the first pixels selected for each partial area.
  • the key image generator 129 for restoration uses first partial regions 412, 416, and 417 among '9' partial regions 411, 412, 413, 414, 415, 416, 417, 418, and 419. , 419), for each of the '5' second subregions 411, 413, 414, 415, and 418, an arbitrary even number of second pixels may be randomly selected for each subregion.
  • the key image generating unit 129 may randomly change a pixel value of each of the second pixels selected for each partial region.
  • the key image generator 129 for restoration changes the pixel values of the first partial regions 412, 416, 417, and 419 and the second partial regions 411, 413, 414, 415, and 418. By doing this, it is possible to generate a key image for restoration.
  • the mapping matrix generator 130 generates the first partial regions 412, 416, and 417 of the '9' partial regions 411, 412, 413, 414, 415, 416, 417, 418, and 419. , 419) by assigning a component of '1' to the same point as the second partial regions 411, 413, 414, 415, and 418), by assigning a component of '0' to the same point, '0' and ' A '3 x 3' mapping matrix consisting of '1' ' can be created.
  • the data set generator 131 checks the 'location information 3' and 'size information 3' included in 'dangerous goods information 3', and creates a data set consisting of 'location information 3' and 'size information 3'. (position information 3, size information 3)'.
  • the substitution matrix generation unit 132 divides the data set into '4' pieces and generates '4' pieces of split data such as 'P 1, P 2, P 3, P 4 ', '5' pieces of dummy data may be randomly generated, such as 'D 1 , D 2 , D 3 , D 4 , D 5 '.
  • the substitution matrix generation unit 132 ' the mapping matrix ' Among the '9' components constituting ', the '4' split data 'P 1, P 2, P 3, P 4 ' are inserted one by one at the point where the components of '1' are located, and '0
  • a '3 x 3' substitution matrix is created. ' can be created.
  • the encrypted image generating unit 133 may generate an encrypted image by encrypting the 'photographed image 3 410' with the 'encryption key 1'.
  • the image transmission unit 134 sends the encrypted image to the manager terminal 160, the substitution matrix ' ' and the key image for restoration may be transmitted.
  • the administrator terminal 160 pre-stores the encryption key in memory, and when the encryption image, the substitution matrix, and the key image for restoration are received from the dangerous materials information management server 110, the encryption key is used to store the encryption key.
  • the second captured image and the key image for restoration are divided into n x n subregions each consisting of n horizontally and n vertically, and For each of the partial regions, the number of pixels having pixel values that do not match between the second captured image and the key image for restoration is checked for each partial region, and the images that do not match each other are identified for each partial region.
  • n ⁇ n size region matrix having the number of pixels having a soma value as a component
  • a modulo-2 operation is performed on each of the components constituting the region matrix.
  • an n x n size restoration matrix composed of '0' and '1' is generated, and when the restoration matrix is generated, the Hadamard product between the restoration matrix and the replacement matrix is calculated and calculated.
  • extracting k elements other than '0' among the n x n elements constituting the operation matrix as the k split data and then combining the extracted k split data to obtain the data set
  • the second location information and the second size information are restored.
  • the modulo-2 operation means an operation of dividing a dividend by 2 and calculating a remainder thereto.
  • the Hadamard product means an operation that multiplies each component in a matrix of the same size.
  • a matrix can be expressed as '[ax by cz]'.
  • n be '3' and k be '4'
  • 'encryption key 1' which is an encryption key pre-shared with the dangerous materials information management server 110, is stored in the memory of the manager terminal 160. It is said that this is pre-stored, and the image transmission unit 134 sends the manager terminal 160, the encrypted image, the substitution matrix ' ' and as the key image for restoration is transmitted, the encrypted image and the substitution matrix ' ' and the key image for restoration is received. Also, assume that the key image for restoration is the same as the picture shown by reference numeral 420 in FIG. 4 .
  • the manager terminal 160 converts the encrypted image to 'encryption key 1'.
  • 'photographed image 3 410' can be restored.
  • the manager terminal 160 divides the 'taken image 3 410' into '9' partial regions 411, 412, 413, 414, 415, 416, 417, 418, 419), and '9' partial regions (421, 422, 423, 424, 425, 426, 427, 428, 429).
  • the manager terminal 160 may check the number of pixels having pixel values that do not coincide with each other between the 'photographed image 3 410' and the key image for restoration 420 in each of '9' subregions.
  • the manager terminal 160 determines pixels having pixel values that do not coincide with each other between 'partial region 1 411' and 'partial region 1 421'. You can check the number as '30'.
  • 'partial area 2 412' constituting 'photographed image 3 410' includes as many as '17 pieces'. Since the pixel values of each of the first pixels are randomly changed, the manager terminal 160 determines the pixels having pixel values that do not coincide with each other between 'partial region 2 412' and 'partial region 2 422'. You can check the number as '17'.
  • the manager terminal 160 determines the number of pixels having pixel values that do not match between 'partial region 3 413' and 'partial region 2 423'. can be identified as '12'.
  • the manager terminal 160 determines the number of pixels having pixel values that do not coincide with each other between 'partial region 4 414' and 'partial region 4 424'. can be identified as '26'.
  • the manager terminal 160 determines the number of pixels having pixel values that do not match between 'partial region 5 415' and 'partial region 5 425'. can be identified as '4'.
  • the manager terminal 160 determines the number of pixels having pixel values that do not match between 'partial region 6 416' and 'partial region 6 426'. can be identified as '21'.
  • the manager terminal 160 determines the number of pixels having pixel values that do not match between 'partial region 7 417' and 'partial region 7 427'. can be identified as '9'.
  • the manager terminal 160 determines the number of pixels having pixel values that do not coincide with each other between 'partial region 8 418' and 'partial region 8 428'. can be identified as '18'.
  • the manager terminal 160 determines the number of pixels having pixel values that do not match between 'partial region 9 419' and 'partial region 9 429'. can be identified as '35'.
  • the manager terminal 160 determines that the number of pixels having pixel values that do not match each other for each subregion is '30, 17, 12, 26, 4, 21, 9, 18, 35 ’, the number of pixels having pixel values that do not match each other identified for each subregion is ‘30, 17, 12, 26, 4, 21, 9, 18, A region matrix of size '3 x 3' with '35' as components, ' ' can be created.
  • the manager terminal 160 uses the region matrix ' By replacing each of the components constituting ' with the result of performing a modulo-2 operation on each component, a '3 x 3' restoration matrix composed of '0' and '1' is ' ' can be created.
  • the manager terminal 160 uses the restoration matrix ' ' and the substitution matrix ' ' Calculate the Hadamard product between ' ', and the operation matrix ' Among the '9' components constituting ', '4' components other than '0' can be extracted as '4' split data.
  • the manager terminal 160 extracts '4' elements other than '0' among the '9' elements constituting the operation matrix as '4' divided data, the direction from the left column to the right column , it is possible to sequentially extract one by one in the direction from the top row to the bottom row.
  • the manager terminal 160 is the operation matrix ' Among the '9' components constituting ', '4' components other than '0' are '1 row 1 column, 1 row 2 columns, 1 row 3 columns, 2 rows 1 column, 2 rows 2 columns, 2 rows By extracting one by one in the order of 3 columns, 3 rows, 1 column, 3 rows, 2 columns, 3 rows, 3 columns, '4' split data, 'P 1, P 2, P 3, P 4 ', can be extracted one by one. there is.
  • the manager terminal 160 restores the data set '(location information 3, size information 3)' by combining 'P 1, P 2, P 3, P 4 ', which is '4' pieces of extracted split data. By doing so, 'position information 3' and 'size information 3' can be restored.
  • FIG. 5 is a flowchart illustrating an operating method of a dangerous substance information management server capable of estimating the actual size of a dangerous object on a road through interworking with an information collection terminal mounted on a vehicle according to an embodiment of the present invention.
  • a plurality of vehicles pre-designated to collect dangerous material information on the road (each of the plurality of vehicles has a camera capable of photographing the front of each vehicle in order to collect dangerous material information on the road) , a camera having a preset first focal length and configured such that an image of a preset first size is formed on the image sensor) and a distance measuring sensor for measuring the distance to a dangerous object in front of each vehicle and the position of each vehicle
  • Hazardous material information collected by an information collection terminal equipped with a GPS capable of collecting information (each of the dangerous material information is photographed on the road taken through an information collection terminal mounted in a vehicle) It maintains a dangerous substance information database in which an image, location information of a point where the photographed image was captured, and size information of a dangerous substance are stored.
  • step S520 a first photographed image of a first dangerous substance is photographed from a first information collection terminal mounted on a first vehicle, which is one of the plurality of vehicles, through a camera provided in the first information collection terminal.
  • the first separation distance between the first vehicle and the first dangerous object measured through a distance measuring sensor provided in the first information collection terminal and the first photographing obtained through a GPS provided in the first information collection terminal.
  • the actual size of the first dangerous object is estimated based on the first focal length and the first separation distance, and then the estimated actual size of the first dangerous object is generated as the first size information for the first dangerous substance.
  • step S530 when the first size information is generated, first dangerous substance information composed of the first photographed image, the first location information, and the first size information is generated, and then stored in the dangerous substance information database. Save dangerous goods information.
  • step S520 when the first captured image, the first separation distance, and the first location information are received from the first information collection terminal, the first captured image adjusting the size of the first dangerous substance to a size corresponding to the first size, which is the size of an image formed on an image sensor of a camera provided in the first information collection terminal; After generating a quadrangular area surrounding the periphery of the object corresponding to , checking the vertical length of the quadrangular area in the resized first captured image, the quadrangular area in the resized first captured image.
  • Equation 1 calculates the actual vertical length of the rectangular region according to Equation 1, calculating the area of the rectangular region in the resized first captured image, and According to the ratio between the vertical length of the blind spot in the adjusted first captured image and the actual vertical length of the blind spot, from the area of the blind spot in the resized first photographed image, and estimating the actual size of the first dangerous object by calculating an actual area, and then generating the estimated actual size of the first dangerous object as the first size information.
  • the operating method of the dangerous substance information management server may include, when the first dangerous substance information is stored in the dangerous substance information database, among the dangerous substance information stored in the dangerous substance information database, the first dangerous substance information 1 determining whether there is dangerous material information overlapping with dangerous material information, and if it is determined that there is dangerous material information overlapping with the first dangerous material information among the dangerous material information stored in the dangerous material information database, the dangerous material The method may further include deleting the first dangerous material information stored in the information database, wherein the step of determining whether or not there is dangerous material information overlapping with the first dangerous material information may include storing the first dangerous material information in the dangerous material information database.
  • the first size information includes location information in which a separation distance from the first location information is within a preset standard distance. Determining whether dangerous material information including size information having a difference between the size and the size of the first position information exists, among the dangerous material information stored in the dangerous material information database, the separation distance from the first location information is If it is confirmed that at least one candidate dangerous substance information exists as dangerous substance information including location information within a standard distance and size information having a difference from the first size information within the standard size, the at least one calculating an image similarity corresponding to each of the at least one candidate dangerous material information by calculating an image similarity between a captured image included in each candidate dangerous material information and the first captured image for each candidate dangerous material information; and When the image similarity corresponding to each of the at least one candidate dangerous substance information is calculated, it is checked whether the image similarity corresponding to each of the at least one candidate dangerous substance information exceeds a preset criterion similarity, and the at least one
  • the step of calculating the image similarity corresponding to each of the at least one candidate dangerous substance information includes a distance from the first location information among the dangerous substance information stored in the dangerous substance information database. It is confirmed that the at least one candidate dangerous substance information exists as dangerous substance information including location information with a distance within the standard distance and size information with a difference from the first size information within the standard size.
  • the operation method of the dangerous materials information management server includes the steps of maintaining an encryption key storage unit in which an encryption key previously shared with an administrator terminal is stored, and the dangerous materials information database from the manager terminal.
  • the second dangerous material information is extracted from the dangerous material information database and a second captured image included in the second dangerous material information is obtained.
  • nxn subregions consisting of n horizontally (n is a natural number equal to or greater than 2) and n vertically; is a natural number less than 2 ) first subregions are randomly selected, and for each of the first subregions, an odd number of first pixels is randomly selected for each subregion, and then, for each subregion, first pixels are randomly selected.
  • a pixel value for each of the selected first pixels is randomly changed, and for each of n 2 -k second subregions other than the first subregions among the nxn subregions, each subregion Generating a key image for restoration by randomly selecting an even number of second pixels for each subregion and then randomly changing a pixel value for each of the second pixels selected for each subregion;
  • an image is generated, by assigning a component of '1' to the same point as the first subregions among the nxn number of subregions and assigning a component of '0' to the same position as the second subregions.
  • mapping matrix composed of '0' and '1'; when the mapping matrix is generated, checking second location information and second size information included in the second dangerous substance information, 2 Generating a data set composed of location information and the second size information, dividing the data set into k pieces to generate k pieces of divided data, randomly generating n 2 -k pieces of dummy data, and then performing the mapping Among the nxn elements constituting the matrix, the k pieces of split data are inserted one by one at the points where elements of '1' are located, and the n 2 -k pieces of dummy data are inserted one by one at the points where elements of '0' are located.
  • the method may further include transmitting, wherein the administrator terminal pre-stores the encryption key in a memory, and the encryption image, the substitution matrix, and the key image for restoration are received from the dangerous substance information management server. Then, after restoring the second captured image by decrypting the encrypted image with the encryption key, the second captured image and the key image for restoration are divided into nxn partial areas each consisting of n horizontally and vertically n areas.
  • the number of pixels having pixel values that do not match between the second captured image and the key image for restoration is checked for each subregion, and the number of pixels is checked for each subregion.
  • a modulo-2 operation is performed on each of the components constituting the region matrix.
  • an nxn size restoration matrix is generated, and when the restoration matrix is generated, a Hadamard product between the restoration matrix and the replacement matrix is calculated to generate an operation matrix, , After extracting k elements other than '0' among the nxn elements constituting the operation matrix as the k divided data, and then combining the extracted k divided data to restore the data set, The second location information and the second size information may be restored.
  • a method of operating a dangerous materials information management server may be implemented as a computer program stored in a storage medium for execution through a combination with a computer.
  • the operating method of the dangerous materials information management server may be implemented in the form of program instructions that can be executed through various computer means and recorded in a computer readable medium.
  • the computer readable medium may include program instructions, data files, data structures, etc. alone or in combination.
  • Program instructions recorded on the medium may be those specially designed and configured for the present invention or those known and usable to those skilled in computer software.
  • Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floptical disks.
  • - includes hardware devices specially configured to store and execute program instructions, such as magneto-optical media, and ROM, RAM, flash memory, and the like.
  • Examples of program instructions include high-level language codes that can be executed by a computer using an interpreter, as well as machine language codes such as those produced by a compiler.

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Abstract

L'invention concerne un serveur de gestion d'informations d'objet dangereux et son procédé de fonctionnement. La présente invention présente un serveur de gestion d'informations d'objet dangereux apte à estimer la taille réelle d'un objet dangereux sur une route conjointement avec un terminal de collecte d'informations monté sur un véhicule, et son procédé de fonctionnement. Ainsi, il est possible de prendre en charge l'acquisition et la gestion d'informations plus précises concernant l'objet dangereux sur la route.
PCT/KR2022/011715 2021-12-30 2022-08-05 Serveur de gestion d'informations d'objet dangereux apte à estimer la taille réelle d'un objet dangereux sur une route conjointement avec un terminal de collecte d'informations monté sur un véhicule, et son procédé de fonctionnement Ceased WO2023128113A1 (fr)

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KR102888399B1 (ko) * 2023-03-24 2025-11-26 주식회사 다리소프트 다중 객체 탐지 모델을 이용하여 도로 상의 위험물 정보를 수집하기 위한 위험물 정보 수집 장치 및 그 동작 방법

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