Complex background PCB mark point image detection method based on Mini ARU-Net network
The invention discloses a complex background printed circuit board mark point image detection method based on a Mini ARU-Net network. The method comprises the following steps: 1) collecting a printedcircuit board image, performing gray processing, extracting a mark point area as a mark point image,...
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creator | WU JINGLI YI GUODONG FENG YANWU |
description | The invention discloses a complex background printed circuit board mark point image detection method based on a Mini ARU-Net network. The method comprises the following steps: 1) collecting a printedcircuit board image, performing gray processing, extracting a mark point area as a mark point image, and adding a binary image of the area where a mark point is located as a segmentation label image;2) constructing a Mini ARUNet network, and inputting a mark point image for training and a segmentation label graph thereof into the Mini ARUNet network for training; 3) inputting a to-be-detected mark point image into the Mini ARUNet network obtained by training in the step 2) to perform mark point segmentation to obtain a segmentation result graph; and 4) solving the centroid of the area where the mark point is located according to the segmentation result graph, taking the centroid as the coordinate of the mark point, solving the average distance from the centroid to the edge of the area where the mark point is locat |
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The method comprises the following steps: 1) collecting a printedcircuit board image, performing gray processing, extracting a mark point area as a mark point image, and adding a binary image of the area where a mark point is located as a segmentation label image;2) constructing a Mini ARUNet network, and inputting a mark point image for training and a segmentation label graph thereof into the Mini ARUNet network for training; 3) inputting a to-be-detected mark point image into the Mini ARUNet network obtained by training in the step 2) to perform mark point segmentation to obtain a segmentation result graph; and 4) solving the centroid of the area where the mark point is located according to the segmentation result graph, taking the centroid as the coordinate of the mark point, solving the average distance from the centroid to the edge of the area where the mark point is locat</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ; PHYSICS</subject><creationdate>2020</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20201225&DB=EPODOC&CC=CN&NR=112132798A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25563,76318</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20201225&DB=EPODOC&CC=CN&NR=112132798A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>WU JINGLI</creatorcontrib><creatorcontrib>YI GUODONG</creatorcontrib><creatorcontrib>FENG YANWU</creatorcontrib><title>Complex background PCB mark point image detection method based on Mini ARU-Net network</title><description>The invention discloses a complex background printed circuit board mark point image detection method based on a Mini ARU-Net network. The method comprises the following steps: 1) collecting a printedcircuit board image, performing gray processing, extracting a mark point area as a mark point image, and adding a binary image of the area where a mark point is located as a segmentation label image;2) constructing a Mini ARUNet network, and inputting a mark point image for training and a segmentation label graph thereof into the Mini ARUNet network for training; 3) inputting a to-be-detected mark point image into the Mini ARUNet network obtained by training in the step 2) to perform mark point segmentation to obtain a segmentation result graph; and 4) solving the centroid of the area where the mark point is located according to the segmentation result graph, taking the centroid as the coordinate of the mark point, solving the average distance from the centroid to the edge of the area where the mark point is locat</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2020</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNizEOwiAUQFkcjHqH7wE60A7qWInGxcYYdW0QvpVQ-AQwenwZPIDTy0vem7KbIBdG_MBdKjtEenkNJ7EFJ6OFQMZnME4OCBozqmzIg8P8JF2GhBqKH4030J6vVYcZPOY3RTtnk4ccEy5-nLHlfncRhwoD9ZiCVFjKXnSc17ypV5t12_zTfAGGdzhV</recordid><startdate>20201225</startdate><enddate>20201225</enddate><creator>WU JINGLI</creator><creator>YI GUODONG</creator><creator>FENG YANWU</creator><scope>EVB</scope></search><sort><creationdate>20201225</creationdate><title>Complex background PCB mark point image detection method based on Mini ARU-Net network</title><author>WU JINGLI ; YI GUODONG ; FENG YANWU</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN112132798A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2020</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>WU JINGLI</creatorcontrib><creatorcontrib>YI GUODONG</creatorcontrib><creatorcontrib>FENG YANWU</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>WU JINGLI</au><au>YI GUODONG</au><au>FENG YANWU</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Complex background PCB mark point image detection method based on Mini ARU-Net network</title><date>2020-12-25</date><risdate>2020</risdate><abstract>The invention discloses a complex background printed circuit board mark point image detection method based on a Mini ARU-Net network. The method comprises the following steps: 1) collecting a printedcircuit board image, performing gray processing, extracting a mark point area as a mark point image, and adding a binary image of the area where a mark point is located as a segmentation label image;2) constructing a Mini ARUNet network, and inputting a mark point image for training and a segmentation label graph thereof into the Mini ARUNet network for training; 3) inputting a to-be-detected mark point image into the Mini ARUNet network obtained by training in the step 2) to perform mark point segmentation to obtain a segmentation result graph; and 4) solving the centroid of the area where the mark point is located according to the segmentation result graph, taking the centroid as the coordinate of the mark point, solving the average distance from the centroid to the edge of the area where the mark point is locat</abstract><oa>free_for_read</oa></addata></record> |
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language | chi ; eng |
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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING IMAGE DATA PROCESSING OR GENERATION, IN GENERAL PHYSICS |
title | Complex background PCB mark point image detection method based on Mini ARU-Net network |
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