CN119127813A

CN119127813A - Image recognition processing system and method based on data analysis

Info

Publication number: CN119127813A
Application number: CN202411219909.6A
Authority: CN
Inventors: 张天舒; 乔琪; 曹珂崯; 许热
Original assignee: Jiangsu Vocational College of Electronics and Information
Current assignee: Jiangsu Vocational College of Electronics and Information
Priority date: 2024-09-02
Filing date: 2024-09-02
Publication date: 2024-12-13
Anticipated expiration: 2044-09-02
Also published as: CN119127813B

Abstract

The invention discloses an image recognition processing system and method based on data analysis, belonging to the field of image processing technology. The image files collected by the maritime radar are classified and compiled, and storage space is allocated to each classification and compilation; the acquisition frequency nodes are unified to form node segments, and the image files collected by the maritime radar in each node segment are uploaded to each image file layer in the service memory; the weight of the memory size of the service memory occupied by each image file layer is counted in real time, and the authority security of each image file layer is evaluated; each image pixel point is identified, and the image bit depth of each image pixel point is recorded; through the image compression iterative analysis method, it is evaluated whether the storage space size of the service memory meets the storage requirements of the image file of the next node segment at the end of the current node segment; after the iteration stops, the storage space size of the service memory is updated, and the storage space size of each classification and compilation is updated.

Description

Image recognition processing system and method based on data analysis

Technical Field

The invention relates to the technical field of image processing, in particular to an image recognition processing system and method based on data analysis.

Background

The pixel point of the image, the pixel point value, the bit depth of the pixel point and the resolution of the image are important consideration factors in image processing and display, wherein the pixel point is a basic unit for forming a digital image, is the smallest controllable light point on a screen and is also the smallest unit in the image, the more the pixel point number is in a display, a digital camera, a video camera and other devices, the finer the detail can be represented, the pixel point value is the color or brightness information represented by each pixel point and is generally represented in a numerical form, the bit depth of the pixel point is the binary bit number used when recording the color or brightness information of each pixel point, and the resolution of the image is the information amount stored in the image, namely, the number of pixel points in each inch of the image is usually represented in PPI (Pixels Per Inch );

In the prior art, the size of the image is generally changed by compressing the number of pixels, but changing the number of pixels tends to lead to shrinking of the display screen, directly affects the size integrity of the display content, so that the display content is lost, and changes the bit depth at the pixels, although the display content can be blurred, the definition of the image data can be ensured to the greatest extent by an effective bit depth adjustment strategy, so as to meet the requirement of the storage space.

Disclosure of Invention

The invention aims to provide an image recognition processing system and method based on data analysis, so as to solve the problems in the background technology.

In order to solve the technical problems, the invention provides the following technical scheme:

The image recognition processing system based on data analysis comprises a service memory module, a storage authority analysis module, an image compression processing analysis module and a service memory updating module;

The system comprises a service memory module, a unified acquisition frequency node, a service memory module and a storage module, wherein the service memory module classifies and compiles image files acquired by the marine radar through the service memory and distributes storage space for each classified and compiles;

The storage authority analysis module counts the weight of the memory size of the service memory occupied by each image file layer in real time when each node section is finished, and evaluates the authority security of each image file layer so as to perform the advance judgment of the compression of the image file strips;

The image compression processing analysis module is used for identifying each image pixel point of each image file and recording the image bit depth of each image pixel point, and evaluating whether the storage space of the service memory meets the storage requirement of the image file of the next node section when the current node section is finished in an image compression iteration analysis mode, if so, stopping iteration, and if not, performing the next iteration until the iteration is stopped when the current node section is met;

And the service memory updating module is used for updating the storage space size of the service memory and updating the storage space size of each classified booklet after iteration is stopped and carrying out image compression iterative analysis on each image file before the next node section is started so as to meet the storage requirement of each image file.

Further, the service memory module comprises a storage space allocation unit and an acquisition behavior configuration unit;

The storage space allocation unit is used for classifying and compiling image files acquired by the marine radars and recording the image files into the service memory, wherein one marine radar corresponds to one classification, and one classification allocates a storage space in the service memory correspondingly;

The acquisition behavior configuration unit is used for unifying acquisition frequency nodes, forming node sections between every two adjacent continuous acquisition frequency nodes, marking any a node section as NS _a, acquiring image files acquired by a marine radar in each node section, uploading the image files to a classified album, automatically distributing image file layers in each storage space by the rear end of a server in a software instruction mode, wherein the image file layers have unique instruction verification attributes of the node sections, and marking the image file layers correspondingly distributed by the node sections NS _a as CB _i|NS_a.

Further, the storage authority analysis module comprises an authority security assessment unit and a prior verification judgment unit;

The authority security evaluation unit is configured to, when each node segment is finished, count in real time a weight value of a memory size of a service memory occupied by each image file layer, and record the weight value as MS (CB _i|NS_a), analyze and evaluate an authority security degree of each image file layer, where a formula is as follows:

Wherein PE (CB _i|NS_a) represents the authority security degree of the image file layer CB _i|NS_a, μ represents the real-time average value of the weight of the memory size of the service memory occupied by each image file layer, and Σ ² represents the real-time variance of the weight of the memory size of the service memory occupied by each image file layer, anA represents the real-time total number of node segments, and I represents the fixed total number of storage spaces;

the pre-verification judging unit is configured to preset a permission security threshold, extract the image file layer CB _i|NS_a if the permission security PE (CB _i|NS_a) of the image file layer CB _i|NS_a is less than or equal to the permission security threshold, or not extract the image file layer CB _i|NS_a.

Further, the image compression processing analysis module comprises a bit depth data acquisition unit and an image compression iteration analysis unit;

The bit depth data acquisition unit is used for identifying each image pixel point of an x-th image file in the extracted image file layer CB _i|NS_a, marking any r-th image pixel point as (CB _i|NS_a, xr), and acquiring the image bit depth of an image pixel point PP _rx(CB_i|NS_a, which is marked as BD (CB _i|NS_a, xr);

the image compression iterative analysis unit is used for establishing an image compression iterative analysis model:

Acquiring all extracted image file layers, and constructing an image file layer sample set to be compressed, wherein the sample set is recorded as SS= { CB _i|NS_a, i epsilon [1, I ], a epsilon [1, A ] };

Recording an image file layer sample set of the t-th iteration as SS _t, arbitrarily selecting an image file layer CB _i|NS_a in the image file layer sample set SS _t, arbitrarily selecting an x-th image file in the image file layer CB _i|NS_a, arbitrarily selecting an image pixel point PP _rx(CB_i|NS_a in the x-th image file), adjusting a bit depth value of the image pixel point PP _rx(CB_i|NS_a), setting an initial adjustment proportion q, and recording an image bit depth after adjustment of the image bit depth BD (CB _i|NS_a, xr) as qBD (CB _i|NS_a, xr);

After the image bit depth is adjusted, returning to and executing the step S2, and updating the authority security PE (CB _i|NS_a) of the image file layer CB _i|NS_a, if the updated authority security is smaller than or equal to the authority security threshold, removing the image file layer CB _i|NS_a from the image file layer sample set SS _t, outputting an iterated image file layer sample set, and recording the image file layer sample set after the t iteration as SS _t+1;

Judging whether the current storage space meets the storage requirement of the image file in the (a+1) th node section NS _a+1, if so, stopping iteration, and if not, performing the (t+1) th iteration, wherein the sample set of the image file layer of the (t+1) th iteration is SS _t+1;

When the t+1st iteration is carried out, the initial adjustment proportion Q is increased, the increase amplitude of the adjustment proportion at each iteration is set to be Q, and when the t+1st iteration is carried out, the set adjustment proportion is q+ (t+1) multiplied by Q;

until it is determined whether the current storage space meets the storage requirement of the image file in the (a+1) th node segment NS _a+1, the iteration is stopped.

An image recognition processing method based on data analysis comprises the following steps:

S1, classifying and compiling image files acquired by a marine radar through a service memory, and distributing storage space for each classified and compiled image file; the unified acquisition frequency node is used for forming node sections, and uploading image files acquired by the maritime radar in each node section to each image file layer in the service memory when each node section is finished;

Step S2, when each node section is finished, counting the weight of the memory size of the service memory occupied by each image file layer in real time, and evaluating the authority security of each image file layer to perform the prior judgment of image file belt compression;

Step S3, identifying each image pixel point of each image file, and recording the image bit depth of each image pixel point; evaluating whether the storage space of the service memory meets the storage requirement of the image file of the next node section when the current node section is finished in an image compression iteration analysis mode, if so, stopping iteration, and if not, performing the next iteration until the storage space of the service memory meets the storage requirement;

And S4, after iteration is stopped, updating the storage space size of the service memory, updating the storage space size of each classified volume, and performing image compression iterative analysis on each image file before the next node section starts so as to meet the storage requirement of each image file.

Further, the implementation process of the step S1 includes:

Step S11, classifying and compiling image files acquired by the marine radars, and recording the image files into a service memory, wherein one marine radar corresponds to one classification, and one classification corresponds to one storage space allocated in the service memory;

Step S12, unifying acquisition frequency nodes, forming node sections between every two adjacent continuous acquisition frequency nodes, marking any a node section as NS _a, acquiring image files acquired by a marine radar in each node section, uploading the image files to a classified catalog, automatically distributing image file layers in each storage space by the rear end of a server in a software instruction mode, wherein the image file layers have unique instruction verification properties of the node sections, and marking the image file layers correspondingly distributed by the node sections NS _a as CB _i|NS_a.

Further, the implementation process of the step S2 includes:

And S21, when each node section is finished, counting the weight of the memory size of the service memory occupied by each image file layer in real time, marking as MS (CB _i|NS_a), analyzing and evaluating the authority security degree of each image file layer, wherein the formula is as follows:

Step S22, presetting a permission safety threshold, extracting the image file layer CB _i|NS_a if the permission safety PE (CB _i|NS_a) of the image file layer CB _i|NS_a is smaller than or equal to the permission safety threshold, otherwise, not extracting the image file layer CB _i|NS_a.

Further, the implementation process of the step S3 includes:

Step S31, identifying each image pixel point of the x-th image file in the extracted image file layer CB _i|NS_a, marking any r-th image pixel point as (CB _i|NS_a, xr), and acquiring the image bit depth of the image pixel point PP _rx(CB_i|NS_a, namely BD (CB _i|NS_a, xr);

step S32, establishing an image compression iterative analysis model:

An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements a data analysis based image recognition processing method as described above when executing the program.

A storage medium containing computer executable instructions which, when executed by a computer processor, are adapted to perform a data analysis based image recognition processing method as described above.

Compared with the prior art, the image recognition processing system and method based on data analysis have the advantages that in the image recognition processing system and method based on data analysis, image files collected by the marine radar are classified and compiled, storage space is allocated for each classified and compiled, unified collection frequency nodes are used for forming node sections, uploading the image files collected by the marine radar in each node section to each image file layer in a service memory, weight of the memory size of the service memory occupied by each image file layer is counted in real time, authority security of each image file layer is evaluated, each image pixel point is recognized, image bit depth of each image pixel point is recorded, whether the storage space size of the service memory meets the storage requirement of an image file of the next node section is evaluated in an image compression iterative analysis mode, after iteration is stopped, the storage space size of the service memory is updated, the storage space size of each classified and compiled is updated, meanwhile, definition of the image data can be ensured maximally.

Drawings

The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:

FIG. 1 is a schematic diagram of an image recognition processing system based on data analysis according to the present invention;

fig. 2 is a schematic diagram of steps of an image recognition processing method based on data analysis according to the present invention.

Detailed Description

The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

Referring to fig. 1, in a first embodiment, an image recognition processing system based on data analysis is provided, the system includes a service memory module, a storage authority analysis module, an image compression processing analysis module and a service memory update module;

preferentially, the service memory module comprises a storage space allocation unit and an acquisition behavior configuration unit;

The acquisition behavior configuration unit is used for unifying acquisition frequency nodes, forming node sections between every two adjacent continuous acquisition frequency nodes, marking any a node section as NS _a, acquiring image files acquired by a marine radar in each node section, uploading the image files to a classified album, automatically distributing image file layers in each storage space by the rear end of a server in a software instruction mode, wherein the image file layers have unique instruction verification attributes of the node sections, and marking the image file layers correspondingly distributed by the node sections NS _a as CB _i|NS_a;

Preferentially, the storage authority analysis module comprises an authority security assessment unit and a prior verification judgment unit;

the pre-verification judging unit is configured to preset a permission security threshold, extract the image file layer CB _i|NS_a if the permission security PE (CB _i|NS_a) of the image file layer CB _i|NS_a is less than or equal to the permission security threshold, or not extract the image file layer CB _i|NS_a;

preferentially, the image compression processing analysis module comprises a bit depth data acquisition unit and an image compression iteration analysis unit;

Until judging whether the current storage space meets the storage requirement of the image files in the (a+1) th node segment NS _a+1 or not, stopping iteration;

Referring to fig. 2, in a second embodiment, an image recognition processing method based on data analysis is provided, and the method includes the following steps:

The method comprises the steps of carrying out classified compiling on image files acquired by the marine radars, and recording the image files into a service memory, wherein one marine radar corresponds to one class, and one class is correspondingly allocated with one storage space in the service memory;

acquiring image files acquired by a marine radar in each node section, uploading the image files to a classified compiling list, automatically distributing image file layers in each storage space by a server rear end in a software instruction mode, wherein the image file layers have unique instruction verification attributes of the node sections, and the image file layers correspondingly distributed by the node sections NS _a are marked as CB _i|NS_a;

Illustratively, at the end of each node segment, the weight of the memory size of the service memory occupied by each image file layer is counted in real time, denoted as MS (CB _i|NS_a), and the authority security of each image file layer is analyzed and evaluated as follows:

Presetting a permission security threshold, extracting an image file layer CB _i|NS_a if the permission security PE (CB _i|NS_a) of the image file layer CS _i|NS_a is smaller than or equal to the permission security threshold, otherwise, not extracting the image file layer CB _i|NS_a;

Illustratively, each image pixel of the x-th image file in the extracted image file layer CB _i|NS_a is identified, any r-th image pixel is noted as (CB _i|NS_a, xr), and the image bit depth of the image pixel PP _rx(CB_i|NS_a is obtained and noted as BD (CB _i|NS_a, xr);

Establishing an image compression iterative analysis model:

An electronic device comprising a memory, a processor and a computer program stored in the memory and operable on the processor, wherein the processor implements a data analysis-based image recognition processing method as described above when executing the program;

A storage medium containing computer executable instructions which, when executed by a computer processor, are adapted to perform a data analysis based image recognition processing method as described above;

By way of example, and not limitation, computer storage media may be employed in any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium can be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium include an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

The computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, etc., or any suitable combination of the foregoing. Computer program code for carrying out operations of the present invention may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).

It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.

It should be noted that the above-mentioned embodiments are merely preferred embodiments of the present invention, and are not intended to limit the present invention, and although the present invention has been described in detail with reference to the above-mentioned embodiments, it will be apparent to those skilled in the art that modifications may be made to the technical solutions described in the above-mentioned embodiments, or equivalents may be substituted for some of the technical features thereof. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An image recognition processing method based on data analysis is characterized by comprising the following steps:

2. The method for processing image recognition based on data analysis according to claim 1, wherein the specific implementation process of step S1 includes:

3. The method for processing image recognition based on data analysis according to claim 2, wherein the specific implementation process of step S2 includes:

4. The method for image recognition processing based on data analysis according to claim 3, wherein the specific implementation process of step S3 includes:

step S32, establishing an image compression iterative analysis model:

5. The image recognition processing system based on data analysis is characterized by comprising a service memory module, a storage authority analysis module, an image compression processing analysis module and a service memory updating module;

6. The image recognition processing system based on data analysis of claim 6, wherein the service memory module comprises a memory space allocation unit and a collection behavior configuration unit;

7. The image recognition processing system based on data analysis of claim 7, wherein the storage authority analysis module comprises an authority security assessment unit and a pre-verification judgment unit;

8. The image recognition processing system based on data analysis of claim 8, wherein the image compression processing analysis module comprises a bit depth data acquisition unit and an image compression iterative analysis unit;

9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements a data analysis based image recognition processing method as claimed in any one of claims 1-4 when executing the program.

10. A storage medium containing computer executable instructions which, when executed by a computer processor, are for performing a data analysis based image recognition processing method as claimed in any one of claims 1 to 4.