CN106548200A - A kind of image comparison system and method - Google Patents
A kind of image comparison system and method Download PDFInfo
- Publication number
- CN106548200A CN106548200A CN201610931011.0A CN201610931011A CN106548200A CN 106548200 A CN106548200 A CN 106548200A CN 201610931011 A CN201610931011 A CN 201610931011A CN 106548200 A CN106548200 A CN 106548200A
- Authority
- CN
- China
- Prior art keywords
- image
- gray level
- level image
- module
- qualified
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
Abstract
The present invention provides a kind of image comparison system and method, and wherein method includes：It is input into each original image；Each original image is processed into into gray level image；The gray level image after process is carried out gray scale with benchmark image respectively to compare；The gray level image for comparing qualified is stored；Underproof gray level image will be compared and do discard processing.This method can quickly compare out difference, and strong applicability has preferable fuzzy recognition comparing power, prevents comparative result from deviation occur to target object in image.
Description
Technical field
The invention mainly relates to image processing field, and in particular to a kind of image comparison system and method.
Background technology
Image comparison system can be used in many commercial production, and at present most common image compares during scheme is movement images
Each pixel value, find out the different region of pixel value, and this scheme that compares be not suitable for most reality due to excessively accurate
Image identification, therefore recognition result is undesirable.
The content of the invention
The technical problem to be solved is to provide a kind of image comparison system and method, quickly can compare out
Difference, strong applicability have preferable fuzzy recognition comparing power, prevent comparative result from deviation occur to target object in image.
The technical scheme that the present invention solves above-mentioned technical problem is as follows：A kind of image comparison system, including：
Data input module, for being input into each original image；
Image processing module, for each original image is processed into gray level image；
Gray scale comparison module, compares for the gray level image after process is carried out gray scale with benchmark image respectively, if ratio
To qualified, then will compare qualified gray level image and send to distance difference comparison module, will otherwise compare underproof gray-scale maps
As doing discard processing；
Distance difference comparison module, for gray scale qualified gray level image to be entered row distance ratio respectively again with benchmark image
It is right, if comparing distance is less than or equal to preset value, distance is compared the original image corresponding to successful gray level image and is sent out
Memory module is delivered to, discard processing is otherwise done；
Memory module, for Memory Reference image and the successful original image of comparison.
The invention has the beneficial effects as follows：Can quickly compare out difference, strong applicability, target object in image is had compared with
Good fuzzy recognition comparing power, prevents comparative result from deviation occur.
On the basis of above-mentioned technical proposal, the present invention can also do following improvement.
Further, the distance difference comparison module includes：
Default unit, compares point for arranging in benchmark image；
Comparing unit, for gray scale qualified gray level image is compared with the click-through row distance that compares in benchmark image, such as
Fruit compares distance and is less than or equal to preset value, then the original image that distance is compared corresponding to qualified gray level image is sent to sending out
Unit is sent, discard processing is otherwise done；
Transmitting element, sends into memory module for will compare qualified original image.
Using the beneficial effect of above-mentioned further scheme it is：Gray proces are carried out, is easy to quickly compare image；Enter
Row distance is compared, and has preferable fuzzy recognition comparing power to target object in image.
Further, also including statistical module, the statistical module connects the gray scale comparison module, and statistical module is used to unite
The number of the gray level image that meter is abandoned.
Another technical scheme that the present invention solves above-mentioned technical problem is as follows：A kind of image comparison method, including following step
Suddenly：
Step S1：It is input into each original image；
Step S2：Each original image is processed into into gray level image；
Step S3：The gray level image after process is carried out gray scale with benchmark image respectively to compare, if comparison is qualified, is held
Row step S4, otherwise execution step S5；
Step S4：The gray level image for comparing qualified is stored；
Step S5：Underproof gray level image will be compared and do discard processing.
On the basis of above-mentioned technical proposal, the present invention can also do following improvement.
Further, the concrete grammar for realizing step S3 is：By comparing in gray scale qualified gray level image and benchmark image
Click through row distance to compare, if comparing distance is less than or equal to preset value, otherwise execution step S4, execution step S5.
Further, also including step S6：The number of the gray level image that statistics is abandoned.
Description of the drawings
Fig. 1 is the module frame chart of image comparison system embodiment of the present invention；
Fig. 2 is the method schematic diagram of image comparison method embodiment of the present invention.
Specific embodiment
The principle and feature of the present invention are described below in conjunction with accompanying drawing, example is served only for explaining the present invention, and
It is non-for limiting the scope of the present invention.
As shown in figure 1, a kind of image comparison system, including：
Data input module, for being input into each original image；
Image processing module, for each original image is processed into gray level image；
Gray scale comparison module, compares for the gray level image after process is carried out gray scale with benchmark image respectively, if ratio
To qualified, then will compare qualified gray level image and send to distance difference comparison module, will otherwise compare underproof gray-scale maps
As doing discard processing；
Distance difference comparison module, for gray scale qualified gray level image to be entered row distance ratio respectively again with benchmark image
It is right, if comparing distance is less than or equal to preset value, distance is compared the original image corresponding to successful gray level image and is sent out
Memory module is delivered to, discard processing is otherwise done；
Memory module, for Memory Reference image and the successful original image of comparison.
Preferably, the distance difference comparison module includes：
Default unit, compares point for arranging in benchmark image；
Comparing unit, for gray scale qualified gray level image is compared with the click-through row distance that compares in benchmark image, such as
Fruit compares distance and is less than or equal to preset value, then the original image that distance is compared corresponding to qualified gray level image is sent to sending out
Unit is sent, discard processing is otherwise done；
Transmitting element, sends into memory module for will compare qualified original image.
Image processing module carries out gray proces, is easy to quickly compare image；Distance difference comparison module is carried out
Distance is compared, and has preferable fuzzy recognition comparing power to target object in image.
Preferably, also including statistical module, the statistical module connects the gray scale comparison module, and statistical module is used to unite
The number of the gray level image that meter is abandoned.
As shown in Fig. 2 a kind of image comparison method, comprises the steps：
Step S1：It is input into each original image；
Step S2：Each original image is processed into into gray level image；
Step S3：The gray level image after process is carried out gray scale with benchmark image respectively to compare, if comparison is qualified, is held
Row step S4, otherwise execution step S5；
Step S4：The gray level image for comparing qualified is stored；
Step S5：Underproof gray level image will be compared and do discard processing.
On the basis of above-mentioned technical proposal, the present invention can also do following improvement.
Further, the concrete grammar for realizing step S3 is：By comparing in gray scale qualified gray level image and benchmark image
Click through row distance to compare, if comparing distance is less than or equal to preset value, otherwise execution step S4, execution step S5.
Further, also including step S6：The number of the gray level image that statistics is abandoned.
The present invention can quickly compare out difference, and strong applicability has preferable fuzzy recognition to target object in image
Comparing power, prevents comparative result from deviation occur.
The foregoing is only presently preferred embodiments of the present invention, not to limit the present invention, all spirit in the present invention and
Within principle, any modification, equivalent substitution and improvements made etc. should be included within the scope of the present invention.
Claims (6)
1. a kind of image comparison system, it is characterised in that include：
Data input module, for being input into each original image；
Image processing module, for each original image is processed into gray level image；
Gray scale comparison module, compares for the gray level image after process is carried out gray scale with benchmark image respectively, if comparing pairing
Lattice, then will compare qualified gray level image and send to distance difference comparison module, will otherwise compare underproof gray level image and do
Discard processing；
Distance difference comparison module, compares for gray scale qualified gray level image is entered row distance with benchmark image again respectively, such as
Fruit compares distance and is less than or equal to preset value, then the original image that distance is compared corresponding to successful gray level image is sent to depositing
Storage module, otherwise does discard processing；
Memory module, for Memory Reference image and the successful original image of comparison.
2. image comparison system according to claim 1, it is characterised in that the distance difference comparison module includes：
Default unit, compares point for arranging in benchmark image；
Comparing unit, for gray scale qualified gray level image is compared with the click-through row distance that compares in benchmark image, if ratio
Adjust the distance less than or equal to preset value, then the original image that distance is compared corresponding to qualified gray level image is sent into single to sending
Unit, otherwise does discard processing；
Transmitting element, sends into memory module for will compare qualified original image.
3. image comparison system according to claim 1, it is characterised in that also including statistical module, the statistical module
Connect the gray scale comparison module, statistical module is used for the number for counting the gray level image for abandoning.
4. a kind of image comparison method, it is characterised in that comprise the steps：
Step S1：It is input into each original image；
Step S2：Each original image is processed into into gray level image；
Step S3：The gray level image after process is carried out gray scale with benchmark image respectively to compare, if comparison is qualified, step is performed
Rapid S4, otherwise execution step S5；
Step S4：The gray level image for comparing qualified is stored；
Step S5：Underproof gray level image will be compared and do discard processing.
5. image comparison method according to claim 4, it is characterised in that the concrete grammar for realizing step S3 is：By ash
The qualified gray level image of degree is compared with the click-through row distance that compares in benchmark image, if comparing distance less than or equal to default
It is worth, then execution step S4, otherwise execution step S5.
6. image comparison method according to claim 4, it is characterised in that also including step S6：The gray scale that statistics is abandoned
The number of image.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610931011.0A CN106548200A (en) | 2016-10-31 | 2016-10-31 | A kind of image comparison system and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610931011.0A CN106548200A (en) | 2016-10-31 | 2016-10-31 | A kind of image comparison system and method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106548200A true CN106548200A (en) | 2017-03-29 |
Family
ID=58393443
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610931011.0A Pending CN106548200A (en) | 2016-10-31 | 2016-10-31 | A kind of image comparison system and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106548200A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107972270A (en) * | 2017-11-16 | 2018-05-01 | 芜湖林电子科技有限公司 | A kind of 3D printer nozzle blocks monitoring system |
| CN108081591A (en) * | 2017-11-16 | 2018-05-29 | 芜湖林电子科技有限公司 | A kind of finished product model categorizing system based on 3D printing |
| CN108127921A (en) * | 2017-11-16 | 2018-06-08 | 芜湖林电子科技有限公司 | A kind of 3D printing finished product model checking method |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101477632A (en) * | 2008-12-19 | 2009-07-08 | 深圳市大族激光科技股份有限公司 | Gray level image matching method and system |
| CN101510257A (en) * | 2009-03-31 | 2009-08-19 | 华为技术有限公司 | Human face similarity degree matching method and device |
| CN101751572A (en) * | 2008-12-05 | 2010-06-23 | 比亚迪股份有限公司 | Pattern detection method, device, equipment and system |
| CN102375987A (en) * | 2010-08-17 | 2012-03-14 | 国基电子（上海）有限公司 | Image processing device and image feature vector extracting and image matching method |
| CN103295022A (en) * | 2012-02-24 | 2013-09-11 | 富泰华工业（深圳）有限公司 | Image similarity calculation system and method |
| CN103870828A (en) * | 2012-12-17 | 2014-06-18 | 富泰华工业（深圳）有限公司 | System and method for judging image similarity degree |
| CN104504375A (en) * | 2014-12-18 | 2015-04-08 | 广州视源电子科技股份有限公司 | Method and device for identifying elements of PCB (Printed Circuit Board) |
-
2016
- 2016-10-31 CN CN201610931011.0A patent/CN106548200A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101751572A (en) * | 2008-12-05 | 2010-06-23 | 比亚迪股份有限公司 | Pattern detection method, device, equipment and system |
| CN101477632A (en) * | 2008-12-19 | 2009-07-08 | 深圳市大族激光科技股份有限公司 | Gray level image matching method and system |
| CN101510257A (en) * | 2009-03-31 | 2009-08-19 | 华为技术有限公司 | Human face similarity degree matching method and device |
| CN102375987A (en) * | 2010-08-17 | 2012-03-14 | 国基电子（上海）有限公司 | Image processing device and image feature vector extracting and image matching method |
| CN103295022A (en) * | 2012-02-24 | 2013-09-11 | 富泰华工业（深圳）有限公司 | Image similarity calculation system and method |
| CN103870828A (en) * | 2012-12-17 | 2014-06-18 | 富泰华工业（深圳）有限公司 | System and method for judging image similarity degree |
| CN104504375A (en) * | 2014-12-18 | 2015-04-08 | 广州视源电子科技股份有限公司 | Method and device for identifying elements of PCB (Printed Circuit Board) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107972270A (en) * | 2017-11-16 | 2018-05-01 | 芜湖林电子科技有限公司 | A kind of 3D printer nozzle blocks monitoring system |
| CN108081591A (en) * | 2017-11-16 | 2018-05-29 | 芜湖林电子科技有限公司 | A kind of finished product model categorizing system based on 3D printing |
| CN108127921A (en) * | 2017-11-16 | 2018-06-08 | 芜湖林电子科技有限公司 | A kind of 3D printing finished product model checking method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110135341B (en) | Weed identification method and device and terminal equipment | |
| CN110032954B (en) | Intelligent identification and counting method and system for reinforcing steel bars | |
| US20210287379A1 (en) | Video data processing method and related apparatus | |
| CN113869293B (en) | Lane line recognition method and device, electronic equipment and computer readable medium | |
| CN112633384A (en) | Object identification method and device based on image identification model and electronic equipment | |
| US9224048B2 (en) | Scene-based people metering for audience measurement | |
| CN106548200A (en) | A kind of image comparison system and method | |
| KR20200145827A (en) | Facial feature extraction model learning method, facial feature extraction method, apparatus, device, and storage medium | |
| US20230093746A1 (en) | Video loop recognition | |
| EP3419253A1 (en) | Data processing method and relevant devices and systems | |
| CN110008821B (en) | Method and equipment for predicting updating of portrait base map | |
| US9812056B2 (en) | Display resolution negotiation | |
| CN108600834B (en) | Video transmission system, receiving/sending/transmitting method and device | |
| CN110992365A (en) | Loss function based on image semantic segmentation and design method thereof | |
| US20130342444A1 (en) | Method and Apparatus for Hand Gesture Trajectory Recognition | |
| EP3968648A1 (en) | Bitrate decision model training method and electronic device | |
| CN111612000B (en) | Commodity classification method and device, electronic equipment and storage medium | |
| US9571744B2 (en) | Video processing method and apparatus | |
| US11232561B2 (en) | Capture and storage of magnified images | |
| CN110267112B (en) | Teaching video display method and device, terminal equipment, server and storage medium | |
| CN110942067A (en) | Text recognition method and device, computer equipment and storage medium | |
| CN111369489B (en) | Image identification method and device and terminal equipment | |
| CN112396016B (en) | Face recognition system based on big data technology | |
| CN110866043A (en) | Data preprocessing method and device, storage medium and terminal | |
| CN110992426A (en) | Gesture recognition method and apparatus, electronic device, and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20170329 |