CN111355900B - Image processing method and device, storage medium and electronic device - Google Patents
Image processing method and device, storage medium and electronic device Download PDFInfo
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- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
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- G08G1/0175—Detecting movement of traffic to be counted or controlled identifying vehicles by photographing vehicles, e.g. when violating traffic rules
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- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
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Abstract
The invention provides an image processing method and device, a storage medium and an electronic device, wherein the method comprises the following steps: acquiring a first image obtained by photographing a target area of a target vehicle; adjusting the brightness of the first image by using the brightness value of the target object in the first image to obtain a second image; comparing the environment brightness value of the environment where the target vehicle is located with a preset environment brightness value to obtain a first comparison result; determining an exposure correction value of the target object using the first comparison result; adjusting the halo of the car lamp equipment in the first image to obtain the adjusted halo of the car lamp equipment; and adjusting the brightness of the target object in the second image based on the exposure correction value and the adjusted halation of the car lamp equipment to obtain a target image. By the method and the device, the problem that the acquired license plate image on the target vehicle is unclear is solved, and the effects of obtaining a clearer target object and ensuring the ambient brightness are achieved.
Description
Technical Field
The present invention relates to the field of communications, and in particular, to an image processing method and apparatus, a storage medium, and an electronic apparatus.
Background
People can feel that a circle of halo or halo is around the car light when driving at night, and the phenomenon should fall into the category of spherical aberration. In the daytime, the pupil of the eye narrows down to a slit that causes light to fall in the center of the lens, and at night, the pupil expands to allow more light to enter the eye, in which case the image of the object seen by the eye falls behind the lens, and the further the image deviates from the lens, the poorer the optical effect. After the imaging deviates from the center of the crystalline lens, light rays cannot be concentrated to the center of eyes, the crystalline lens is round, so that a circular halo is seen, and a camera is similar to a human eye and can form a large circle of halo at a car lamp after exposure. The halo can cause great interference to a camera for shooting a license plate, the reflection performance of the automobile license plate is high, if the automobile license plate is not mastered well, the image of the license plate becomes dark under the action of a front light, or the license plate becomes white under the irradiation of a light source of the camera, so that the phenomenon that only the license plate is seen and no number is seen occurs.
In view of the above technical problems, no effective solution has been proposed in the related art.
Disclosure of Invention
The embodiment of the invention provides an image processing method and device, a storage medium and an electronic device, and aims to at least solve the problem that a license plate image on a target vehicle acquired in the related art is unclear.
According to an embodiment of the present invention, there is provided an image processing method including: acquiring a first image obtained by photographing a target area of a target vehicle; adjusting the brightness of the first image by using the brightness value of the target object in the first image to obtain a second image; comparing the environment brightness value of the environment where the target vehicle is located with a preset environment brightness value to obtain a first comparison result; determining an exposure correction value of the target object using the first comparison result; adjusting the halo of the car lamp equipment in the first image to obtain the adjusted halo of the car lamp equipment; and adjusting the brightness of the target object in the second image based on the exposure correction value and the adjusted halation of the vehicle lamp equipment to obtain a target image.
According to another embodiment of the present invention, there is provided an image processing apparatus including: a first acquisition module configured to acquire a first image obtained by photographing a target area of a target vehicle; the first determining module is used for adjusting the brightness of the first image by using the brightness value of the target object in the first image to obtain a second image; the first comparison module is used for comparing the environment brightness value of the environment where the target vehicle is located with a preset environment brightness value to obtain a first comparison result; a second determining module for determining an exposure correction value of the target object using the first comparison result; the first adjusting module is used for adjusting the halation of the car lamp equipment in the first image to obtain the adjusted halation of the car lamp equipment; and the third determining module is used for adjusting the brightness of the target object in the second image based on the exposure correction value and the adjusted halation of the car lamp equipment to obtain a target image.
Optionally, the apparatus further comprises: the identification module is used for identifying the halo emitted by the lamp equipment in the target vehicle from the first image before the brightness value of the target object in the first image is used for adjusting the brightness of the first image to obtain a second image; a fourth determining module, configured to perform halo processing on the first image to determine a halo center of the halo, where the halo processing includes binarization processing and connected region processing on the first image; and the fifth determining module is used for determining the target object by utilizing the halo center.
Optionally, the first determining module includes: a first determination unit configured to determine a luminance average value of the target object from luminance values of the target object; the second determining unit is used for comparing the brightness average value of the target object with a first preset threshold value to obtain a second comparison result; and a third determining unit configured to adjust the brightness of the first image based on the second comparison result to obtain the second image.
Optionally, the first determining module includes one of: a fourth determining unit, configured to increase the exposure luminance of the first image to obtain the second image when the luminance average value of the target object is smaller than the lower limit of the first preset threshold; and a fifth determining unit configured to reduce the exposure luminance of the first image to obtain the second image when the average luminance value of the target object is greater than the upper limit value of the first preset threshold.
Optionally, the first comparing module includes: a sixth determining unit configured to determine an average value of the brightness of the environment from the brightness values of the environment; a seventh determining unit, configured to compare the brightness average value of the environment with the preset environment brightness value, so as to obtain the first comparison result.
Optionally, the second determining module includes one of: an eighth determining unit, configured to determine an initial exposure correction value of the target object as the exposure correction value when an environment luminance value of the environment is smaller than the preset environment luminance value and a luminance average value of the target object is within a preset luminance tolerance range; a ninth determining unit configured to determine the exposure correction value using the environment luminance value if the environment luminance value of the environment is smaller than the preset environment luminance value and the luminance average value of the target object is not within a preset luminance tolerance range, wherein the exposure correction value is a positive number.
Optionally, the second determining module includes one of: a tenth determining unit configured to determine an initial exposure correction value of the target object as the exposure correction value in a case where an environment luminance value of the environment is greater than or equal to the preset environment luminance value and a luminance average value of the target object is within a preset luminance tolerance range; an eleventh determining unit configured to determine the exposure correction value using an environment luminance value of the environment when the environment luminance value is greater than or equal to the preset environment luminance value and a luminance average value of the target object is not within a preset luminance tolerance range, wherein the exposure correction value is a negative number.
Optionally, the third determining module includes one of: a boosting unit, configured to boost an exposure luminance of a target object in the second image in a backlight scene so that a luminance value of the target object is within a preset luminance tolerance range, when the exposure correction value is a positive number and an environment luminance value of the environment is less than a preset environment luminance value; and a reducing unit, configured to reduce the exposure brightness of the target object in the second image in the front-lighting scene so that the brightness value of the target object is within a preset brightness tolerance range when the exposure correction value is a negative value and the ambient brightness value of the environment is greater than or equal to a preset ambient brightness value.
Optionally, the apparatus further comprises: a sixth determining module, configured to adjust brightness of a target object in the second image based on the exposure correction value to obtain a target image, and then convert the target image into an image in a color space HSV domain to obtain an HSV image; and the processing module is used for performing brightness processing on the brightness V channel in the HSV image so as to adjust the halation of the vehicle lamp equipment in the target image and obtain the adjusted halation of the vehicle lamp equipment.
Optionally, the processing unit includes: a first determining subunit, configured to perform area division on halos of the vehicle lamp device to obtain N halo areas, where N is a natural number greater than or equal to 1, and brightness ranges of V channels in the N halo areas are different; a second determining subunit, configured to determine a weight of each halo region in the N halo regions, to obtain N weights; a third determining subunit, configured to correct the N weights by using a weight of an adjacent halo region of each halo region in the N halo regions, to obtain N corrected weights; and the compensation subunit is used for performing brightness compensation on the halo regions corresponding to the N corrected weights so as to adjust the halo of the vehicle lamp device in the target image, so as to obtain the adjusted halo of the vehicle lamp device.
Optionally, the apparatus comprises: a seventh determining module, configured to perform brightness compensation on the halo regions corresponding to the N corrected weights, so as to convert the target image into a color mode RGB domain after adjusting halos of the vehicle lighting devices in the target image, and obtain an RGB image; and the output module is used for outputting the RGB image.
According to a further embodiment of the present invention, there is also provided a storage medium having a computer program stored therein, wherein the computer program is configured to perform the steps of any of the above method embodiments when executed.
According to yet another embodiment of the present invention, there is also provided an electronic device, including a memory and a processor, the memory having a computer program stored therein, the processor being configured to execute the computer program to perform the steps in any of the method embodiments.
According to the invention, the first image obtained by shooting the target area of the target vehicle is obtained; adjusting the brightness of the first image by using the brightness value of the target object in the first image to obtain a second image; comparing the environment brightness value of the environment where the target vehicle is located with a preset environment brightness value to obtain a first comparison result; determining an exposure correction value of the target object using the first comparison result; and adjusting the halo of the vehicle lamp equipment in the first image to obtain the adjusted halo of the vehicle lamp equipment, and adjusting the brightness of the target object in the second image based on the exposure correction value and the adjusted halo of the vehicle lamp equipment to obtain the target image. The purpose of adjusting the exposure of the target object by combining the brightness, the ambient brightness and the halo of the target object can be achieved. Therefore, the problem that the license plate image on the target vehicle acquired in the related technology is unclear can be solved, and the effects of obtaining a clearer target object and ensuring the ambient brightness can be achieved.
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The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
fig. 1 is a block diagram of a hardware configuration of a mobile terminal of an image processing method according to an embodiment of the present invention;
FIG. 2 is a flow chart of an image processing method according to an embodiment of the present invention;
FIG. 3 is a schematic size diagram of a target vehicle according to an embodiment of the invention;
FIG. 4 is a flowchart of an environmental scenario determination according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a channel process according to an alternative embodiment of the present invention;
FIG. 6 is an overall flow chart according to an alternative embodiment of the present invention;
fig. 7 is a block diagram of the structure of an image processing apparatus according to an embodiment of the present invention.
Detailed Description
The invention will be described in detail hereinafter with reference to the accompanying drawings in conjunction with embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
The method provided by the first embodiment of the present application may be executed in a mobile terminal, a computer terminal, or a similar computing device. Taking the mobile terminal as an example, fig. 1 is a block diagram of a hardware structure of the mobile terminal of an image processing method according to an embodiment of the present invention. As shown in fig. 1, the mobile terminal 10 may include one or more (only one shown in fig. 1) processors 102 (the processor 102 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data, and optionally may also include a transmission device 106 for communication functions and an input-output device 108. It will be understood by those skilled in the art that the structure shown in fig. 1 is only an illustration, and does not limit the structure of the mobile terminal. For example, the mobile terminal 10 may also include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1.
The memory 104 may be used to store a computer program, for example, a software program of an application software and a module, such as a computer program corresponding to the image processing method in the embodiment of the present invention, and the processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, so as to implement the method described above. The memory 104 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory located remotely from the processor 102, which may be connected to the mobile terminal 10 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission device 106 is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the mobile terminal 10. In one example, the transmission device 106 includes a Network adapter (NIC), which can be connected to other Network devices through a base station so as to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.
In the present embodiment, an image processing method is provided, and fig. 2 is a flowchart of an image processing method according to an embodiment of the present invention, and as shown in fig. 2, the flowchart includes the steps of:
step S202, acquiring a first image obtained by shooting a target area of a target vehicle;
optionally, in this embodiment, the target area includes, but is not limited to, a portion of a headlight of the target vehicle, including a license plate and the headlight of the target object, and further including other components around the vehicle.
Step S204, brightness adjustment is carried out on the first image by utilizing the brightness value of the target object in the first image to obtain a second image;
step S206, comparing the environment brightness value of the environment where the target vehicle is located with a preset environment brightness value to obtain a first comparison result;
step S208, determining an exposure correction value of the target object by using the first comparison result;
step S210, adjusting the halation of the car lamp equipment in the first image to obtain the adjusted halation of the car lamp equipment;
and step S212, adjusting the brightness of the target object in the second image based on the exposure correction value and the adjusted halation of the car lamp device to obtain a target image.
Through the above steps, since the first image obtained by photographing the target area of the target vehicle is acquired; adjusting the brightness of the first image by using the brightness value of the target object in the first image to obtain a second image; comparing the environment brightness value of the environment where the target vehicle is located with a preset environment brightness value to obtain a first comparison result; determining an exposure correction value of the target object using the first comparison result; and adjusting the halo of the vehicle lamp equipment in the first image to obtain the adjusted halo of the vehicle lamp equipment, and adjusting the brightness of the target object in the second image based on the exposure correction value and the adjusted halo of the vehicle lamp equipment to obtain the target image. The purpose of adjusting the exposure of the target object by combining the brightness, the ambient brightness and the halo of the target object can be achieved. Therefore, the problem that the license plate image on the target vehicle acquired in the related technology is unclear can be solved, and the effects of obtaining a clearer target object and ensuring the ambient brightness can be achieved.
Alternatively, the execution subject of the above steps may be a terminal or the like, but is not limited thereto.
In an optional embodiment, before the brightness adjustment of the first image is performed by using the brightness value of the target object in the first image to obtain the second image, the method further includes:
s1, identifying the halo emitted by the lamp equipment in the target vehicle from the first image;
s2, performing halo processing on the first image to determine a halo center of the halo, wherein the halo processing comprises binarization processing and connected region processing on the first image;
and S3, determining the target object by using the halo center.
Alternatively, in this embodiment, the center of the halo of the vehicle lamp device may be determined by a binarization method and a connected domain method, the approximate position of the target object may be determined from the central point, and the luminance value of the target object may be calculated.
For example, a target vehicle to be identified is determined by a vehicle detector, and a size diagram of the target vehicle is intercepted, wherein the size diagram is as shown in fig. 3, so that the whole vehicle is ensured to be in the size diagram and properly comprises the peripheral environment information of the target vehicle. Determining the A point and the B point of the car lamp halo center through a binarization method and a connected domain method, determining the approximate position K of the license plate frame according to the A, B points, and calculating the brightness mean value Ev _ car of the K.
Through the embodiment, the target object can be accurately determined through the halo center, and the subsequent processing of the exposure of the target object is facilitated.
In an optional embodiment, performing brightness adjustment on the first image by using the brightness value of the target object in the first image to obtain the second image includes:
s1, determining the average brightness value of the target object from the brightness values of the target object;
s2, comparing the brightness average value of the target object with a first preset threshold value to obtain a second comparison result;
s3, adjusting the brightness of the first image based on the second comparison result to obtain a second image.
Optionally, in this embodiment, the first preset threshold is a set of value intervals.
In an alternative embodiment, the adjusting the brightness of the first image based on the second comparison result to obtain the second image comprises one of the following:
s1, under the condition that the brightness average value of the target object is smaller than the lower limit value of the first preset threshold value, improving the exposure brightness of the first image to obtain a second image;
s2, when the average brightness value of the target object is greater than the upper limit value of the first preset threshold, the exposure brightness of the first image is reduced to obtain a second image.
Optionally, in this embodiment, when the average brightness value of the target object is smaller than the lower limit of the first preset threshold, it indicates that the target object is too dark, and the exposure brightness value of the whole image needs to be increased. When the average brightness value of the target object is larger than the upper limit value of the first preset threshold, the target object is over-bright, and the exposure brightness value of the whole image needs to be reduced.
Alternatively, for example, the calculated license plate brightness Ev _ car is compared with preset threshold intervals T1 and T2, and if Ev _ car is smaller than T1, it represents that the license plate is too dark and the exposure brightness Ev value of the whole image needs to be increased, and if Ev _ car is larger than T2, it represents that the license plate is too bright and the exposure brightness Ev value of the whole image needs to be decreased. Through the adjustment of the exposure brightness of the whole image, the license plate brightness Ev _ car falls in a threshold value interval, and the preliminary threshold value is set to be larger and is easier to fall in.
In an optional embodiment, comparing the environmental brightness value of the environment where the target vehicle is located with a preset environmental brightness value to obtain a first comparison result, includes:
s1, determining the average brightness value of the environment from the brightness value of the environment;
and S2, comparing the brightness average value of the environment with a preset environment brightness value to obtain a first comparison result.
Optionally, in this embodiment, the preset environment brightness value may be an interval value.
In an alternative embodiment, determining the exposure correction value for the target object using the first comparison result includes one of:
s1, determining the initial exposure correction value of the target object as the exposure correction value under the condition that the environment brightness value of the environment is smaller than the preset environment brightness value and the brightness average value of the target object is within the preset brightness tolerance range;
and S2, determining an exposure correction value by using the environment brightness value under the condition that the environment brightness value of the environment is less than the preset environment brightness value and the brightness average value of the target object is not within the preset brightness tolerance range, wherein the exposure correction value is a positive number.
Alternatively, in the present embodiment, in the case where the ambient brightness value of the environment is smaller than the preset ambient brightness value, the ambient brightness is darker than the desired brightness. In the case where the ambient brightness value of the environment is less than the preset ambient brightness value, the ambient brightness is brighter than the desired brightness.
In an alternative embodiment, determining the exposure correction value for the target object using the first comparison result includes one of:
s1, determining the initial exposure correction value of the target object as the exposure correction value under the condition that the environment brightness value of the environment is greater than or equal to the preset environment brightness value and the brightness average value of the target object is within the preset brightness tolerance range;
and S2, determining an exposure correction value by using the environment brightness value under the condition that the environment brightness value of the environment is greater than or equal to the preset environment brightness value and the brightness average value of the target object is not within the preset brightness tolerance range, wherein the exposure correction value is a negative number.
Optionally, for example, comparing the current ambient brightness Ev with the expected brightness Ev _ def, if Ev < Ev _ def and the ambient brightness is darker than the expected brightness, determining whether the license plate brightness Ev _ car is within an adjustment tolerance [ diff _ min, diff _ max ], if so, not needing to Correct the exposure parameter, if not, indicating that the current license plate brightness is increasingly darker, calculating an exposure correction value Correct according to the ambient scene, where the value is a positive number; if Ev is greater than Ev _ def and the ambient brightness is brighter than the expected brightness, judging whether the license plate brightness Ev _ car is within the adjustment tolerance [ diff _ min, diff _ max ], if so, not needing to Correct the exposure parameters, if not, indicating that the current license plate brightness is brighter and brighter, calculating the exposure correction value Correct according to the ambient scene, wherein the value is a negative number. The ambient brightness EV value is newly updated according to the exposure correction value.
In an alternative embodiment, the brightness of the target object in the second image is adjusted based on the exposure correction value and the adjusted halo of the vehicular lamp device to obtain the target image, and the method includes one of the following steps:
s1, under the condition that the exposure correction value is positive and the environmental brightness value of the environment is less than the preset environmental brightness value, the exposure brightness of the target object in the second image in the backlight scene is improved so that the brightness value of the target object is within the preset brightness tolerance range;
and S2, in the case that the exposure correction value is negative and the environmental brightness value of the environment is greater than or equal to the preset environmental brightness value, reducing the exposure brightness of the target object in the second image in the taillight scene so that the brightness value of the target object is within the preset brightness tolerance range.
Optionally, in this embodiment, when the brightness of the target object is adjusted, a scene where the target object is located may be determined, and a scene determination may be performed according to the current license plate exposure correction value and the current environment brightness value, where an environment scene determination flowchart is shown in fig. 4, when the current license plate exposure correction value Correct is a positive number and the environment brightness Ev value is much smaller than the expected brightness Ev _ def value, it is determined that the current environment scene is a strong backlight scene, and the environment exposure needs to be promoted until the license plate brightness falls within an allowable tolerance range [ diff _ min, diff _ max ], and a specific backlight scene Gamma1 is selected, where the Gamma1 is mainly used to reduce a highlight region after the promotion of the exposure; when the current license plate exposure correction value Correct is negative and the ambient brightness Ev value is far greater than the expected brightness Ev _ def value, judging that the current ambient scene is a stronger front light scene, reducing the ambient exposure until the license plate brightness falls within an allowable tolerance range [ diff _ min, diff _ max ], and selecting a specific front light scene Gamma2, wherein the Gamma2 is mainly used for increasing the darker area after low exposure; and after Gamma debugging is completed, optimizing the brightness of the whole image.
In an optional embodiment, the halo of the vehicular lamp device in the first image is adjusted to obtain the adjusted halo of the vehicular lamp device, and the method further includes:
s1, converting the target image into an image of a color space (HSV) domain to obtain an HSV image;
and S2, performing brightness processing on the brightness V channel in the HSV image to adjust the halo of the vehicle lamp device in the target image to obtain the adjusted halo of the vehicle lamp device.
In an optional embodiment, performing brightness processing on the brightness V channel in the HSV image to adjust the halo of the vehicle lamp device in the target image, so as to obtain an adjusted halo of the vehicle lamp device, includes:
s1, dividing the area of the halo of the car lamp equipment to obtain N halo areas, wherein N is a natural number which is greater than or equal to 1, and the lightness ranges of V channels in the N halo areas are different;
s2, determining the weight of each halo region in the N halo regions to obtain N weights;
s3, correcting the N weights by using the weight of the adjacent halo region of each halo region in the N halo regions to obtain N corrected weights;
and S4, performing brightness compensation on the halo regions corresponding to the N corrected weights to adjust the halos of the car light equipment in the target image, so as to obtain the halos of the car light equipment after adjustment.
In an optional embodiment, after performing brightness compensation on the halo regions corresponding to the N corrected weights to adjust the halo of the car light device in the target image and obtain the adjusted halo of the car light device, the method further includes:
s1, converting the target image into a color mode RGB domain to obtain an RGB image;
s2, outputting the RGB image.
Optionally, in this embodiment, after the exposure brightness and the license plate brightness of the whole image are adjusted, the vehicle lamp halo of the vehicle lamp needs to be filtered as much as possible, in order to save resources, the halo removing module is performed in the captured vehicle size image, the red, green, blue, RGB domain is converted into the hue saturation value HSV domain, and only the brightness channel V domain is processed, as shown in fig. 5, in the direction from the farthest point C to the center point a of the halo, the outer ring of the halo is defined as W1, the middle ring is defined as W2, the inner ring is defined as W3, where W3 mainly includes points where the V channel values are all 220 to 255, W2 includes points where the V channel values are all 180 to 220, and W1 includes points where the V channel values are all less than 180. The division of the circle is only one area division, which does not affect the subsequent calculation, so that points which do not meet the conditions of the circle in W1, W2 and W3 may exist, and only show the trend of light.
The linear weight distribution is carried out from the farthest point C to the point A of the halo center, the weight is larger when the point C is closer, and the weight is smaller when the point A is closer, for example: one point in the W circle is P (V), the Weight of the point is Weight, the P point adjacent point P (V), the Weight of the point is Weight, the distance between the three points and the C point is P < P < P, so that Weight > Weight, and the corrected point on P is P _ new (V _ new) (P (V) × Weight + P (V) × Weight)/2, and the P point adjacent point P is corrected to be P _ new (V _ new) ((V _ new) (+ P (V) ×) Weight + P (V) (. WEight)). And starting to perform primary correction to the inner ring by using a point of which the periphery is not polluted by the white light of the vehicle lamp.
And performing compensation correction on the preliminary correction point, namely replacing the value by using a proper pixel brightness value of a peripheral point, sorting the brightness data of a neighborhood 3X3 window by taking the current processing point as a center, such as P2_ new (V2_ new), replacing the correction value by using a second largest value if the current processing point is the largest value and the absolute difference value of the second largest value is greater than a set threshold value T3, and otherwise, outputting the original value. And performing brightness compensation correction for the second time, converting the HSV domain into the RGB domain for display output, and finishing the halo reducing module.
In summary, after the environment brightness and the license plate brightness are primarily adjusted and optimized according to different scenes, part of car light halos are filtered by a weight method, and then the subsequent license plate grabbing work can be better completed.
The present invention will be described in detail with reference to the following specific examples:
the embodiment mainly provides a method for correcting the environment brightness and the license plate brightness after scene judgment and then using a weight method to reduce halation so as to assist in license plate snapshot. The overall flow chart is shown in fig. 6, and is mainly divided into the following parts: extracting key information, primarily adjusting brightness, judging scenes and reducing halation, and specifically comprises the following steps:
s601: the vehicle detector is used for finding a target vehicle;
s602: intercepting a vehicle dimension diagram;
s603: determining halo centers A and B by a binarization and connected domain method;
s604: determining a license plate frame K according to the AB point, and calculating a brightness mean value Ev _ car of the K;
s605: comparing Ev _ car to a threshold interval [ T1, T2 ];
s606: when Ev _ car is smaller than T1, raising the EV value of the whole image exposure brightness;
s607: when Ev _ car is larger than T2, the whole image exposure brightness EV value is reduced;
s608: the ambient brightness EV is compared with the desired brightness EV _ def;
s609: under the condition that the ambient brightness EV is equal to the expected brightness Ev _ def, the original exposure parameters are reserved;
s610: when the ambient brightness EV is smaller than the expected brightness Ev _ def, judging whether Ev _ car is within the adjustment tolerance [ diff _ min, diff _ max ];
s611: when the Ev _ car is not within the adjustment tolerance [ diff _ min, diff _ max ], the Ev _ car indicates that the brightness is reduced, and exposure correction is performed according to the environmental scene;
s612: when the Ev _ car is within the adjustment tolerance [ diff _ min, diff _ max ], the original exposure parameters are reserved;
s613: when the ambient brightness EV is larger than the expected brightness Ev _ def, judging whether Ev _ car is within the adjustment tolerance [ diff _ min, diff _ max ];
s614: when the Ev _ car is not within the adjustment tolerance [ diff _ min, diff _ max ], the Ev _ car indicates that the brightness is reduced, and exposure correction is performed according to the environmental scene;
s615: if the Ev _ car is not within the adjustment tolerance [ diff _ min, diff _ max ], the original exposure parameters are reserved;
s616: running whole graph optimization;
s617: carrying out weight halo removal;
s618: and extracting the license plate.
Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
In this embodiment, an image processing apparatus is further provided, and the apparatus is used to implement the foregoing embodiments and preferred embodiments, and the description of the apparatus is omitted for brevity. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.
Fig. 7 is a block diagram of the structure of an image processing apparatus according to an embodiment of the present invention, as shown in fig. 7, the apparatus including:
a first acquisition module 72 for acquiring a first image obtained by photographing a target area of a target vehicle;
a first determining module 74, configured to perform brightness adjustment on the first image by using a brightness value of a target object in the first image to obtain a second image;
a first comparing module 76, configured to compare an environment brightness value of an environment where the target vehicle is located with a preset environment brightness value, so as to obtain a first comparison result;
a second determination module 78 for determining an exposure correction value of the target object using the first comparison result;
a first adjusting module 710, configured to adjust a halo of the car light device in the first image, to obtain an adjusted halo of the car light device;
and a third determining module 712, configured to adjust the brightness of the target object in the second image based on the exposure correction value and the adjusted halo of the vehicle lamp device, so as to obtain a target image.
Optionally, the apparatus further comprises:
the identification module is used for identifying the halo emitted by the lamp equipment in the target vehicle from the first image before the brightness value of the target object in the first image is used for adjusting the brightness of the first image to obtain a second image;
a fourth determining module, configured to perform halo processing on the first image to determine a halo center of the halo, where the halo processing includes binarization processing and connected region processing on the first image;
and the fifth determining module is used for determining the target object by utilizing the halo center.
Optionally, the first determining module includes:
a first determination unit configured to determine a luminance average value of the target object from luminance values of the target object;
the second determining unit is used for comparing the brightness average value of the target object with a first preset threshold value to obtain a second comparison result;
and a third determining unit configured to adjust the brightness of the first image based on the second comparison result to obtain the second image.
Optionally, the first determining module includes one of:
a fourth determining unit, configured to increase the exposure luminance of the first image to obtain the second image when the luminance average value of the target object is smaller than the lower limit of the first preset threshold;
and a fifth determining unit configured to reduce the exposure luminance of the first image to obtain the second image when the average luminance value of the target object is greater than the upper limit value of the first preset threshold.
Optionally, the first comparing module includes:
a sixth determining unit configured to determine an average value of the brightness of the environment from the brightness values of the environment;
a seventh determining unit, configured to compare the brightness average value of the environment with the preset environment brightness value, so as to obtain the first comparison result.
Optionally, the second determining module includes one of:
an eighth determining unit, configured to determine an initial exposure correction value of the target object as the exposure correction value when an environment luminance value of the environment is smaller than the preset environment luminance value and a luminance average value of the target object is within a preset luminance tolerance range;
a ninth determining unit configured to determine the exposure correction value using the environment luminance value if the environment luminance value of the environment is smaller than the preset environment luminance value and the luminance average value of the target object is not within a preset luminance tolerance range, wherein the exposure correction value is a positive number.
Optionally, the second determining module includes one of:
a tenth determining unit configured to determine an initial exposure correction value of the target object as the exposure correction value in a case where an environment luminance value of the environment is greater than or equal to the preset environment luminance value and a luminance average value of the target object is within a preset luminance tolerance range;
an eleventh determining unit configured to determine the exposure correction value using an environment luminance value of the environment when the environment luminance value is greater than or equal to the preset environment luminance value and a luminance average value of the target object is not within a preset luminance tolerance range, wherein the exposure correction value is a negative number.
Optionally, the third determining module includes one of:
a boosting unit, configured to boost an exposure luminance of a target object in the second image in a backlight scene so that a luminance value of the target object is within a preset luminance tolerance range, when the exposure correction value is a positive number and an environment luminance value of the environment is less than a preset environment luminance value;
and a reducing unit, configured to reduce the exposure brightness of the target object in the second image in the front-lighting scene so that the brightness value of the target object is within a preset brightness tolerance range when the exposure correction value is a negative value and the ambient brightness value of the environment is greater than or equal to a preset ambient brightness value.
Optionally, the apparatus further comprises:
a sixth determining module, configured to adjust brightness of a target object in the second image based on the exposure correction value to obtain a target image, and then convert the target image into an image in a color space HSV domain to obtain an HSV image;
and the processing module is used for performing brightness processing on the brightness V channel in the HSV image so as to adjust the halation of the vehicle lamp equipment in the target image and obtain the adjusted halation of the vehicle lamp equipment.
Optionally, the processing unit includes:
a first determining subunit, configured to perform area division on halos of the vehicle lamp device to obtain N halo areas, where N is a natural number greater than or equal to 1, and brightness ranges of V channels in the N halo areas are different;
a second determining subunit, configured to determine a weight of each halo region in the N halo regions, to obtain N weights;
a third determining subunit, configured to correct the N weights by using a weight of an adjacent halo region of each halo region in the N halo regions, to obtain N corrected weights;
and the compensation subunit is used for performing brightness compensation on the halo regions corresponding to the N corrected weights so as to adjust the halo of the vehicle lamp device in the target image, so as to obtain the adjusted halo of the vehicle lamp device.
Optionally, the apparatus comprises:
a seventh determining module, configured to perform brightness compensation on the halo regions corresponding to the N corrected weights, so as to convert the target image into a color mode RGB domain after adjusting halos of the vehicle lighting devices in the target image, and obtain an RGB image;
and the output module is used for outputting the RGB image.
It should be noted that, the above modules may be implemented by software or hardware, and for the latter, the following may be implemented, but not limited to: the modules are all positioned in the same processor; alternatively, the modules are respectively located in different processors in any combination.
Embodiments of the present invention also provide a storage medium having a computer program stored therein, wherein the computer program is arranged to perform the steps of any of the above method embodiments when executed.
Alternatively, in the present embodiment, the storage medium may be configured to store a computer program for executing the steps of:
s1, acquiring a first image obtained by photographing a target area of a target vehicle;
s2, adjusting the brightness of the first image by using the brightness value of the target object in the first image to obtain a second image;
s3, comparing the environment brightness value of the environment where the target vehicle is located with a preset environment brightness value to obtain a first comparison result;
s4, determining the exposure correction value of the target object by using the first comparison result;
s5, adjusting the halo of the car lamp equipment in the first image to obtain the adjusted halo of the car lamp equipment;
and S6, adjusting the brightness of the target object in the second image based on the exposure correction value and the adjusted halation of the vehicle lamp device to obtain a target image.
Optionally, in this embodiment, the storage medium may include, but is not limited to: various media capable of storing computer programs, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.
Embodiments of the present invention also provide an electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the above method embodiments.
Optionally, the electronic apparatus may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.
Optionally, in this embodiment, the processor may be configured to execute the following steps by a computer program:
s1, acquiring a first image obtained by photographing a target area of a target vehicle;
s2, adjusting the brightness of the first image by using the brightness value of the target object in the first image to obtain a second image;
s3, comparing the environment brightness value of the environment where the target vehicle is located with a preset environment brightness value to obtain a first comparison result;
s4, determining the exposure correction value of the target object by using the first comparison result;
s5, adjusting the halo of the car lamp equipment in the first image to obtain the adjusted halo of the car lamp equipment;
and S6, adjusting the brightness of the target object in the second image based on the exposure correction value and the adjusted halation of the vehicle lamp device to obtain a target image.
Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation manners, and this embodiment is not described herein again.
It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the principle of the present invention should be included in the protection scope of the present invention.
Claims (14)
1. An image processing method, comprising:
acquiring a first image obtained by photographing a target area of a target vehicle;
adjusting the brightness of the first image by using the brightness value of the target object in the first image to obtain a second image;
comparing the environment brightness value of the environment where the target vehicle is located with a preset environment brightness value to obtain a first comparison result;
determining an exposure correction value of the target object using the first comparison result;
adjusting the brightness of a target object in the second image based on the exposure correction value to obtain a first target image;
and adjusting the halo of the car lamp equipment in the first target image to obtain a second target image.
2. The method of claim 1, wherein before adjusting the brightness of the first image using the brightness value of the target object in the first image to obtain the second image, the method further comprises:
identifying, from the first image, a halo emitted by a vehicular light device in the target vehicle;
performing halo processing on the first image to determine a halo center of the halo, wherein the halo processing comprises binarization processing and connected region processing on the first image;
and determining the target object by using the halo center.
3. The method of claim 1, wherein adjusting the brightness of the first image using the brightness value of the target object in the first image to obtain a second image comprises:
determining the average brightness value of the target object from the brightness values of the target object;
comparing the brightness average value of the target object with a first preset threshold value to obtain a second comparison result;
and adjusting the brightness of the first image based on the second comparison result to obtain the second image.
4. The method of claim 3, wherein adjusting the brightness of the first image based on the second comparison results to obtain the second image comprises one of:
under the condition that the brightness average value of the target object is smaller than the lower limit value of the first preset threshold, improving the exposure brightness of the first image to obtain a second image;
and under the condition that the brightness average value of the target object is larger than the upper limit value of the first preset threshold, reducing the exposure brightness of the first image to obtain the second image.
5. The method according to claim 1, wherein comparing an environment brightness value of an environment in which the target vehicle is located with a preset environment brightness value to obtain the first comparison result comprises:
determining an average brightness value of the environment from the brightness values of the environment;
and comparing the brightness average value of the environment with the preset environment brightness value to obtain the first comparison result.
6. The method of claim 1, wherein determining the exposure correction value for the target object using the first comparison result comprises one of:
determining an initial exposure correction value of the target object as the exposure correction value under the condition that the environment brightness value of the environment is smaller than the preset environment brightness value and the brightness average value of the target object is within a preset brightness tolerance range;
and under the condition that the environment brightness value of the environment is smaller than the preset environment brightness value and the brightness average value of the target object is not within a preset brightness tolerance range, determining the exposure correction value by using the environment brightness value, wherein the exposure correction value is a positive number.
7. The method of claim 1, wherein determining the exposure correction value for the target object using the first comparison result comprises one of:
determining an initial exposure correction value of the target object as the exposure correction value under the condition that the environment brightness value of the environment is greater than or equal to the preset environment brightness value and the brightness average value of the target object is within a preset brightness tolerance range;
and under the condition that the environment brightness value of the environment is greater than or equal to the preset environment brightness value and the brightness average value of the target object is not within a preset brightness tolerance range, determining the exposure correction value by using the environment brightness value, wherein the exposure correction value is a negative number.
8. The method of claim 1, wherein adjusting the brightness of the target object in the second image based on the exposure correction value to obtain the first target image comprises one of:
under the condition that the exposure correction value is positive and the environment brightness value of the environment is smaller than a preset environment brightness value, improving the exposure brightness of the target object in the second image in a backlight scene to enable the brightness value of the target object to be within a preset brightness tolerance range, and obtaining the first target image;
and under the condition that the exposure correction value is a negative number and the environment brightness value of the environment is greater than or equal to a preset environment brightness value, reducing the exposure brightness of the target object in the second image in the taillight scene so that the brightness value of the target object is within a preset brightness tolerance range to obtain the first target image.
9. The method of claim 1, wherein adjusting the halo of the vehicular light device in the first target image to obtain a second target image comprises:
converting the first target image into an image of a color space (HSV) domain to obtain an HSV image;
and performing brightness processing on a brightness V channel in the HSV image to adjust the halation of the car lamp equipment in the first target image to obtain the second target image.
10. The method of claim 9, wherein performing brightness processing on a brightness V channel in the HSV image to adjust a halo of a vehicle light device in the first target image to obtain the second target image comprises:
dividing the halation of the car lamp equipment into N halation areas, wherein N is a natural number which is greater than or equal to 1, and the brightness ranges of V channels in the N halation areas are different;
determining the weight of each halo region in the N halo regions to obtain N weights;
correcting the N weights by using the weight of the adjacent halo region of each halo region in the N halo regions to obtain N corrected weights;
and performing brightness compensation on the halo regions corresponding to the N corrected weights to adjust halos of the car lamp equipment in the first target image to obtain the second target image.
11. The method according to claim 10, wherein after performing brightness compensation on the halo regions corresponding to the N corrected weights to adjust the halo of the car light device in the first target image to obtain the second target image, the method further comprises:
converting the first target image into a color mode RGB domain to obtain an RGB image;
and outputting the RGB image.
12. An image processing apparatus characterized by comprising:
a first acquisition module configured to acquire a first image obtained by photographing a target area of a target vehicle;
the first determining module is used for adjusting the brightness of the first image by using the brightness value of the target object in the first image to obtain a second image;
the first comparison module is used for comparing the environment brightness value of the environment where the target vehicle is located with a preset environment brightness value to obtain a first comparison result;
a second determination module, configured to determine an exposure correction value of the target object using the first comparison result;
the first adjusting module is used for adjusting the brightness of a target object in the second image based on the exposure correction value to obtain a first target image;
and the third determining module is used for adjusting the halation of the car lamp equipment in the first target image to obtain a second target image.
13. A storage medium, in which a computer program is stored, wherein the computer program is arranged to perform the method of any of claims 1 to 11 when executed.
14. An electronic device comprising a memory and a processor, wherein the memory has stored therein a computer program, and wherein the processor is arranged to execute the computer program to perform the method of any of claims 1 to 11.
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