CN112001905A - Household product damage detection system and detection method based on image processing - Google Patents
Household product damage detection system and detection method based on image processing Download PDFInfo
- Publication number
- CN112001905A CN112001905A CN202010850094.7A CN202010850094A CN112001905A CN 112001905 A CN112001905 A CN 112001905A CN 202010850094 A CN202010850094 A CN 202010850094A CN 112001905 A CN112001905 A CN 112001905A
- Authority
- CN
- China
- Prior art keywords
- picture
- image
- image processing
- module
- electrically connected
- 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
- 238000001514 detection method Methods 0.000 title claims abstract description 53
- 238000006243 chemical reaction Methods 0.000 claims description 10
- 238000000605 extraction Methods 0.000 claims description 10
- 230000008054 signal transmission Effects 0.000 claims description 10
- 238000000034 method Methods 0.000 claims description 8
- 238000012797 qualification Methods 0.000 abstract description 3
- 238000010586 diagram Methods 0.000 description 4
- 230000018109 developmental process Effects 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/90—Determination of colour characteristics
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
- G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30204—Marker
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Biochemistry (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Health & Medical Sciences (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Quality & Reliability (AREA)
- Signal Processing (AREA)
- Geometry (AREA)
- Image Analysis (AREA)
Abstract
The invention discloses a household product damage detection system and a household product damage detection method based on image processing, relates to the technical field of digital image processing, and aims to solve the problems that in the prior art, the qualification rate of household products is generally judged only by manual detection, and the efficiency is low. The image processing system comprises an image acquisition module, wherein the output end of the image acquisition module is electrically connected with the input end of an industrial host, the output end of the industrial host is electrically connected with the input end of a router, the output end of the router is electrically connected with the input end of an image processing terminal, the image processing terminal comprises an image brightness processing module, a digital image processing module and an image scanning library, the output end of the image scanning library is electrically connected with the input end of the image brightness processing module, and the output end of the image brightness processing module is electrically connected with the input end of the digital image processing module.
Description
Technical Field
The invention relates to the technical field of digital image processing, in particular to a household product damage detection system and a household product damage detection method based on image processing.
Background
Digital image processing is a method and technique for performing processes such as denoising, enhancement, restoration, segmentation, feature extraction, and the like on an image by a computer. The generation and rapid development of digital image processing is largely influenced by three factors: the development of computers; secondly, the development of mathematics; and thirdly, the application requirements of wide agriculture and animal husbandry, forestry, environment, military, industry, medicine and the like are increased.
The household products are partially damaged when leaving the factory, but in the prior art, the qualification rate of the household products is judged only by manual detection, so that the efficiency is low; therefore, the existing requirements are not met, and a household product damage detection system and a household product damage detection method based on image processing are provided.
Disclosure of Invention
The invention aims to provide a household product damage detection system and a household product damage detection method based on image processing, and aims to solve the problems that the prior art provided in the background art generally only depends on manual detection to judge the qualification rate of household products and is low in efficiency.
In order to achieve the purpose, the invention provides the following technical scheme: the household product damage detection system based on image processing comprises a picture acquisition module, wherein the output end of the picture acquisition module is electrically connected with the input end of an industrial host, the output end of the industrial host is electrically connected with the input end of a router, and the output end of the router is electrically connected with the input end of an image processing terminal.
Preferably, the image processing terminal comprises an image brightness processing module, a digital image processing module and an image scanning library, wherein an output end of the image scanning library is electrically connected with an input end of the image brightness processing module, and an output end of the image brightness processing module is electrically connected with an input end of the digital image processing module.
Preferably, the digital image processing module includes a picture pixel extraction module, a suspicious pixel marking module and a damaged area calculation module, an output end of the picture pixel extraction module is electrically connected with an input end of the suspicious pixel marking module, and an output end of the suspicious pixel marking module is electrically connected with an input end of the damaged area calculation module.
Preferably, the image acquisition module comprises a lens, an image sensor, an analog signal processing circuit, an analog-to-digital conversion circuit, a main CPU, a data signal processing circuit and a signal transmission circuit, wherein the output end of the lens is electrically connected with the input end of the image sensor, the output end of the image sensor is electrically connected with the input end of the analog signal processing circuit, the output end of the analog signal processing circuit is electrically connected with the input end of the analog-to-digital conversion circuit, the output end of the analog-to-digital conversion circuit is electrically connected with the output ends of the main CPU and the data signal processing circuit, and the output ends of the main CPU and the data signal processing circuit are electrically connected with the input end of the industrial host through the signal transmission.
Preferably, the input end of the lens is electrically connected with the output ends of the exposure system and the focusing system.
Preferably, the detection method of the household product breakage detection system based on image processing includes the following steps:
step 1: acquiring a detection picture of a household product to be detected through a picture acquisition module, and transmitting the detection picture to an industrial host through a signal transmission circuit;
step 2: the industrial host further uploads the image information to the image processing terminal by using the router at the output end;
and step 3: a picture scanning library is arranged in the image processing terminal, factory standard pictures of household products are arranged in the picture scanning library, the detected pictures uploaded in the step 2 are adjusted by using an image brightness processing module, so that the brightness and the contrast of the detected pictures are consistent with the factory standard pictures, and errors in comparison are reduced;
and 4, step 4: importing the adjusted detection picture and the factory standard picture into a digital image processing module, and comparing the two pictures;
and 5: after comparison, separating different areas in the picture by using a picture pixel extraction module, displaying in a black-and-white mode, reversing, making the white part transparent, and marking the rest parts with a suspicious pixel marking module to be red, wherein the red area is a damaged area of the household product;
step 6: converting the standard picture into a gray-scale picture which is used as a base picture and integrated with the red area picture so as to conveniently view the damaged part of the furniture;
and 7: and the damaged area calculating module is used for further calculating the pixel number of the red area so as to obtain the damaged area of the household product, and the damaged household product can be conveniently and timely repaired by adopting a proper repairing method.
Preferably, in the step 1, the lens of the image acquisition module needs to adjust the exposure and the focal length of the image by using an exposure system and a focusing system, so that the exposure and the focal length are consistent with the parameters of the outgoing standard picture of the home product in the picture scanning library, thereby ensuring the accuracy of subsequent detection.
Preferably, the image brightness processing module in step 3 is implemented based on a program, and the contrast and brightness parameters of the standard picture and the detected picture can be adjusted to be consistent by using the image-adjusting-matching color function in the program.
Preferably, the digital image processing module in the step 4-7 is implemented based on a Python system, and the implemented path is to display different areas in a black and white manner, reverse the display, change the white portion into a transparent state, mark the remaining portion with red, process the remaining portion with red, use a standard picture as a base picture, convert the base picture into a gray-scale picture, integrate the red area picture with the base picture, and calculate the area of the red area through the damaged area calculation module, thereby obtaining the damaged area of the home product.
Compared with the prior art, the invention has the beneficial effects that:
the invention obtains the detecting picture of the household product to be detected by adopting the picture collecting module, and transmits the detecting picture to the industrial host computer by the signal transmission circuit, the industrial host computer further transmits the detecting picture to the image processing terminal by the router, the image processing terminal is internally provided with the picture scanning library, the scanning library is the factory standard picture of the household product, the detecting picture can be compared with the detecting picture, before the comparison, firstly, the detecting picture is adjusted by the image brightness processing module, the brightness and the contrast are consistent with the parameters of the factory standard picture, so as to reduce the error of the subsequent comparison, then, the two pictures are compared by the digital image processing module, different areas in the pictures are separated by the picture pixel extracting module, the display is carried out by a black and white mode, the reverse direction is taken, the white part is changed to be transparent, the rest part is marked with red by the suspicious pixel marking module, so as to realize the positioning work of, at the moment, the red area is the damaged area of the household product, then the gray-scale image of the standard picture is used as the base image and integrated with the red area image, the pixel area of the red area is further calculated through the damaged area calculating module, the damaged degree of the household product can be visually obtained, the damaged household product can be conveniently and timely repaired by adopting a proper repairing method, and compared with conventional manual detection, the detection efficiency is higher and more accurate.
Drawings
FIG. 1 is a schematic diagram of a detection system of the present invention;
FIG. 2 is a schematic diagram of an internal structure of the image processing terminal according to the present invention;
FIG. 3 is a schematic diagram of an internal structure of the digital image processing module according to the present invention;
FIG. 4 is a schematic diagram of an internal structure of the image capture module according to the present invention;
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
Referring to fig. 1-4, an embodiment of the present invention is shown: the household product damage detection system based on image processing comprises a picture acquisition module, wherein the output end of the picture acquisition module is electrically connected with the input end of an industrial host, the output end of the industrial host is electrically connected with the input end of a router, and the output end of the router is electrically connected with the input end of an image processing terminal.
Further, the image processing terminal comprises an image brightness processing module, a digital image processing module and an image scanning library, wherein the output end of the image scanning library is electrically connected with the input end of the image brightness processing module, the output end of the image brightness processing module is electrically connected with the input end of the digital image processing module, and a nondestructive standard image shot when the household product leaves a factory is arranged in the image scanning library, so that the comparison with a subsequent detection image is convenient.
Furthermore, the digital image processing module comprises a picture pixel extraction module, a suspicious pixel marking module and a damaged area calculation module, wherein the output end of the picture pixel extraction module is electrically connected with the input end of the suspicious pixel marking module, the output end of the suspicious pixel marking module is electrically connected with the input end of the damaged area calculation module, and the image brightness processing module can adjust the detection image to ensure that the contrast and the brightness of the detection image are consistent with those of the standard image so as to reduce the error of subsequent detection.
Further, the image collecting module comprises a lens, an image sensor, an analog signal processing circuit, an analog-to-digital conversion circuit, a main CPU, a data signal processing circuit and a signal transmission circuit, wherein the output end of the lens is electrically connected with the input end of the image sensor, the output end of the image sensor is electrically connected with the input end of the analog signal processing circuit, the output end of the analog signal processing circuit is electrically connected with the input end of the analog-to-digital conversion circuit, the output end of the analog-to-digital conversion circuit is electrically connected with the output end of the main CPU and the output end of the data signal processing circuit, the output ends of the main CPU and the data signal processing circuit are electrically connected with the input end of the industrial host through the signal transmission circuit, the image sensor, the analog signal processing circuit and the analog-to-digital conversion circuit cooperate to complete the image collecting work, and, the signal is transmitted to the industrial host by the signal transmission circuit.
Furthermore, the input end of the lens is electrically connected with the output ends of the exposure system and the focusing system, and the exposure system and the focusing system are used for controlling the exposure and the focal length of the lens, so that the difference of parameters between the detected picture and the standard picture is reduced, and the accuracy of subsequent detection is improved.
Further, the detection method of the household product damage detection system based on image processing comprises the following steps:
step 1: acquiring a detection picture of a household product to be detected through a picture acquisition module, and transmitting the detection picture to an industrial host through a signal transmission circuit;
step 2: the industrial host further uploads the image information to the image processing terminal by using the router at the output end;
and step 3: a picture scanning library is arranged in the image processing terminal, factory standard pictures of household products are arranged in the picture scanning library, the detected pictures uploaded in the step 2 are adjusted by using an image brightness processing module, so that the brightness and the contrast of the detected pictures are consistent with the factory standard pictures, and errors in comparison are reduced;
and 4, step 4: importing the adjusted detection picture and the factory standard picture into a digital image processing module, and comparing the two pictures:
and 5: after comparison, different areas in the picture are separated by using the picture pixel extraction module, the picture is displayed in a black-and-white mode, the direction is reversed, the white part is changed into transparent, the rest part is marked with red by using the suspicious pixel marking module, and at the moment, the red area is a damaged area of the household product:
step 6: converting the standard picture into a gray-scale picture which is used as a base picture and integrated with the red area picture so as to conveniently view the damaged part of the furniture;
and 7: and the damaged area calculating module is used for further calculating the pixel number of the red area so as to obtain the damaged area of the household product, and the damaged household product can be conveniently and timely repaired by adopting a proper repairing method.
Further, in step 1, the lens of the image acquisition module needs to adjust the exposure and the focal length of the image by using an exposure system and a focusing system, so that the exposure and the focal length are consistent with the parameters of the outgoing standard picture of the home product in the picture scanning library, and the accuracy of subsequent detection is ensured.
Further, the image brightness processing module in step 3 is realized based on a program, and the contrast and brightness parameters of the standard picture and the detected picture can be adjusted to be consistent by using the image-adjusting-color matching function in the program.
Further, the digital image processing module in the step 4-7 is realized based on a Python system, and the realized path is that different areas are displayed in a black and white mode, the reverse direction is taken, the white part is changed into transparent, the rest part is marked with red for processing, then a standard picture is used as a base picture and is converted into a gray scale picture, the red area picture and the base picture are integrated, and the area of the red area is calculated through the damaged area calculating module, so that the damaged area of the household product is obtained.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (9)
1. Damaged detecting system of house product based on image processing, including picture collection module, its characterized in that: the output end of the picture acquisition module is electrically connected with the input end of the industrial host, the output end of the industrial host is electrically connected with the input end of the router, and the output end of the router is electrically connected with the input end of the image processing terminal.
2. The image processing-based household product breakage detection system according to claim 1, characterized in that: the image processing terminal comprises an image brightness processing module, a digital image processing module and an image scanning library, wherein the output end of the image scanning library is electrically connected with the input end of the image brightness processing module, and the output end of the image brightness processing module is electrically connected with the input end of the digital image processing module.
3. The image processing-based household product breakage detection system according to claim 2, characterized in that: the digital image processing module comprises an image pixel extraction module, a suspicious pixel marking module and a damaged area calculation module, wherein the output end of the image pixel extraction module is electrically connected with the input end of the suspicious pixel marking module, and the output end of the suspicious pixel marking module is electrically connected with the input end of the damaged area calculation module.
4. The image processing-based household product breakage detection system according to claim 1, characterized in that: the image acquisition module comprises a lens, an image sensor, an analog signal processing circuit, an analog-to-digital conversion circuit, a main CPU, a data signal processing circuit and a signal transmission circuit, wherein the output end of the lens is electrically connected with the input end of the image sensor, the output end of the image sensor is electrically connected with the input end of the analog signal processing circuit, the output end of the analog signal processing circuit is electrically connected with the input end of the analog-to-digital conversion circuit, the output end of the analog-to-digital conversion circuit is electrically connected with the output ends of the main CPU and the data signal processing circuit, and the output ends of the main CPU and the data signal processing circuit are electrically connected with the input end of the industrial host through the signal.
5. The image processing-based household product breakage detection system according to claim 4, characterized in that: the input end of the lens is electrically connected with the output ends of the exposure system and the focusing system.
6. The detection method of the image processing-based household product breakage detection system according to any one of claims 1 to 5, characterized by comprising the following steps:
step 1: acquiring a detection picture of a household product to be detected through a picture acquisition module, and transmitting the detection picture to an industrial host through a signal transmission circuit;
step 2: the industrial host further uploads the image information to the image processing terminal by using the router at the output end;
and step 3: a picture scanning library is arranged in the image processing terminal, factory standard pictures of household products are arranged in the picture scanning library, the detected pictures uploaded in the step 2 are adjusted by using an image brightness processing module, so that the brightness and the contrast of the detected pictures are consistent with the factory standard pictures, and errors in comparison are reduced;
and 4, step 4: importing the adjusted detection picture and the factory standard picture into a digital image processing module, and comparing the two pictures;
and 5: after comparison, separating different areas in the picture by using a picture pixel extraction module, displaying in a black-and-white mode, reversing, making the white part transparent, and marking the rest parts with a suspicious pixel marking module to be red, wherein the red area is a damaged area of the household product;
step 6: converting the standard picture into a gray-scale picture which is used as a base picture and integrated with the red area picture so as to conveniently view the damaged part of the furniture;
and 7: and the damaged area calculating module is used for further calculating the pixel number of the red area so as to obtain the damaged area of the household product, and the damaged household product can be conveniently and timely repaired by adopting a proper repairing method.
7. The detection method of the image processing-based household product breakage detection system according to claim 6, characterized in that: in the step 1, the lens of the image acquisition module needs to adjust the exposure and the focal length of the image by using an exposure system and a focusing system, so that the exposure and the focal length are consistent with the parameters of the outgoing standard picture of the household product in the picture scanning library, and the accuracy of subsequent detection is ensured.
8. The detection method of the image processing-based household product breakage detection system according to claim 6, characterized in that: the image brightness processing module in the step 3 is realized based on a program, and the contrast and brightness parameters of the standard picture and the detected picture can be adjusted to be consistent by using the image-adjusting-color matching function in the program.
9. The detection method of the image processing-based household product breakage detection system according to claim 6, characterized in that: the digital image processing module in the steps 4 to 7 is realized based on a Python system, and the realized path is that different areas are displayed in a black and white mode, the reverse direction is taken, the white part is changed into transparent, the rest part is marked with red, then a standard picture is used as a base picture and is converted into a gray scale picture, the red area picture is integrated with the base picture, and the area of the red area is calculated through a damaged area calculating module, so that the damaged area of the household product is obtained.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202010850094.7A CN112001905A (en) | 2020-08-21 | 2020-08-21 | Household product damage detection system and detection method based on image processing |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202010850094.7A CN112001905A (en) | 2020-08-21 | 2020-08-21 | Household product damage detection system and detection method based on image processing |
Publications (1)
Publication Number | Publication Date |
---|---|
CN112001905A true CN112001905A (en) | 2020-11-27 |
Family
ID=73473655
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202010850094.7A Pending CN112001905A (en) | 2020-08-21 | 2020-08-21 | Household product damage detection system and detection method based on image processing |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN112001905A (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN115908422A (en) * | 2023-01-10 | 2023-04-04 | 吉林省信息技术研究所 | Equipment quality detection device and method based on image recognition |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101514966A (en) * | 2009-03-20 | 2009-08-26 | 何流 | Industrial line scanning intelligent camera |
CN107203990A (en) * | 2017-04-02 | 2017-09-26 | 南京汇川图像视觉技术有限公司 | A kind of labeling damage testing method based on template matches and image quality measure |
CN109782707A (en) * | 2018-12-24 | 2019-05-21 | 北京航天智造科技发展有限公司 | A kind of industry spot monitoring method suitable for industry internet |
-
2020
- 2020-08-21 CN CN202010850094.7A patent/CN112001905A/en active Pending
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101514966A (en) * | 2009-03-20 | 2009-08-26 | 何流 | Industrial line scanning intelligent camera |
CN107203990A (en) * | 2017-04-02 | 2017-09-26 | 南京汇川图像视觉技术有限公司 | A kind of labeling damage testing method based on template matches and image quality measure |
CN109782707A (en) * | 2018-12-24 | 2019-05-21 | 北京航天智造科技发展有限公司 | A kind of industry spot monitoring method suitable for industry internet |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN115908422A (en) * | 2023-01-10 | 2023-04-04 | 吉林省信息技术研究所 | Equipment quality detection device and method based on image recognition |
CN115908422B (en) * | 2023-01-10 | 2023-12-29 | 吉林省信息技术研究所 | Equipment quality detection device and method based on image recognition |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN101770582B (en) | Image matching system and method | |
JP3951984B2 (en) | Image projection method and image projection apparatus | |
CN103424409B (en) | Vision detecting system based on DSP | |
CN110991360B (en) | Robot inspection point position intelligent configuration method based on visual algorithm | |
JP2020197797A (en) | Image processing device and image processing method | |
CN116721107B (en) | Intelligent monitoring system for cable production quality | |
CN108871185B (en) | Method, device and equipment for detecting parts and computer readable storage medium | |
CN105574161A (en) | Trademark graph element identification method, device and system | |
CN106845314B (en) | A kind of method for rapidly positioning of two dimensional code | |
CN103729631A (en) | Vision-based connector surface feature automatically-identifying method | |
CN113996500A (en) | Intelligent dispensing identification system based on visual dispensing robot | |
CN111157532A (en) | Visual detection device and method for scratches of mobile phone shell | |
CN112001905A (en) | Household product damage detection system and detection method based on image processing | |
CN116758063B (en) | Workpiece size detection method based on image semantic segmentation | |
KR102642691B1 (en) | apparatus for recognizing measurement value and correcting distortion of instrument panel image and camera | |
CN116664817A (en) | Power device state change detection method based on image difference | |
CN115479891A (en) | Automatic detection system and method for circuit board mounted components based on image recognition | |
CN116259008A (en) | Water level real-time monitoring method based on computer vision | |
CN111815552A (en) | Workpiece detection method and device, readable storage medium and terminal equipment | |
KR101766787B1 (en) | Image correction method using deep-learning analysis bassed on gpu-unit | |
CN111428796B (en) | General object detection method and system based on deep learning | |
CN103279953A (en) | Machine vision calibration system based on LabVIEW platform | |
CN112444302B (en) | Image acquisition device, water level detection device, method and storage medium | |
CN101794373B (en) | Application method of rotating and sub-pixel matching algorithm to machine vision system | |
CN209086155U (en) | High-precision silk-screen deflection sensing device |
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 |