Large skin edge defect detection method based on multi-scale neighborhood
The invention discloses a large skin edge defect detection method based on a multi-scale neighborhood. According to the method, a multi-scale space search method is constructed, space information of corresponding key points is better judged, the search direction is optimized and three-dimensional po...
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| creator | NIE JINGMOU XIE HE LIU XUEBING MAO JIANXU FENG MINGTAO ZHU QING WU ZIJIE WANG YAONAN |
| description | The invention discloses a large skin edge defect detection method based on a multi-scale neighborhood. According to the method, a multi-scale space search method is constructed, space information of corresponding key points is better judged, the search direction is optimized and three-dimensional point cloud edge points are recognized on the basis of the space information, the operation efficiency of three-dimensional image edge recognition is greatly improved, and the recognition success rate is increased; and meanwhile, ordering the extracted boundary points, and detecting defects by using the change of a mask characteristic value. According to the method, edge defect detection of the point cloud image can be more accurately realized in a shorter time, and the method has extremely high algorithm robustness and can be applied to the field of precision detection with large scale, complex structure and high efficiency requirement.
本发明公开了一种基于多尺度邻域的大型蒙皮边缘缺陷检测方法。该方法通过构建一种多尺度空间搜索方法，更好的判断对应关键点的空间信息，并以此为依据优化搜索方向以及识别 |
| format | Patent |
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本发明公开了一种基于多尺度邻域的大型蒙皮边缘缺陷检测方法。该方法通过构建一种多尺度空间搜索方法，更好的判断对应关键点的空间信息，并以此为依据优化搜索方向以及识别</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ; PHYSICS</subject><creationdate>2022</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=20220531&DB=EPODOC&CC=CN&NR=114565629A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76289</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20220531&DB=EPODOC&CC=CN&NR=114565629A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>NIE JINGMOU</creatorcontrib><creatorcontrib>XIE HE</creatorcontrib><creatorcontrib>LIU XUEBING</creatorcontrib><creatorcontrib>MAO JIANXU</creatorcontrib><creatorcontrib>FENG MINGTAO</creatorcontrib><creatorcontrib>ZHU QING</creatorcontrib><creatorcontrib>WU ZIJIE</creatorcontrib><creatorcontrib>WANG YAONAN</creatorcontrib><title>Large skin edge defect detection method based on multi-scale neighborhood</title><description>The invention discloses a large skin edge defect detection method based on a multi-scale neighborhood. According to the method, a multi-scale space search method is constructed, space information of corresponding key points is better judged, the search direction is optimized and three-dimensional point cloud edge points are recognized on the basis of the space information, the operation efficiency of three-dimensional image edge recognition is greatly improved, and the recognition success rate is increased; and meanwhile, ordering the extracted boundary points, and detecting defects by using the change of a mask characteristic value. According to the method, edge defect detection of the point cloud image can be more accurately realized in a shorter time, and the method has extremely high algorithm robustness and can be applied to the field of precision detection with large scale, complex structure and high efficiency requirement.
本发明公开了一种基于多尺度邻域的大型蒙皮边缘缺陷检测方法。该方法通过构建一种多尺度空间搜索方法，更好的判断对应关键点的空间信息，并以此为依据优化搜索方向以及识别</description><subject>CALCULATING</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>2022</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZPD0SSxKT1Uozs7MU0hNAbJSUtNSk0uAVAmQyszPU8hNLcnIT1FISixOTVEA8UtzSjJ1i5MTc1IV8lIz0zOS8osy8vNTeBhY0xJzilN5oTQ3g6Kba4izh25qQX58anFBYnJqXmpJvLOfoaGJqZmpmZGlozExagCw0jRy</recordid><startdate>20220531</startdate><enddate>20220531</enddate><creator>NIE JINGMOU</creator><creator>XIE HE</creator><creator>LIU XUEBING</creator><creator>MAO JIANXU</creator><creator>FENG MINGTAO</creator><creator>ZHU QING</creator><creator>WU ZIJIE</creator><creator>WANG YAONAN</creator><scope>EVB</scope></search><sort><creationdate>20220531</creationdate><title>Large skin edge defect detection method based on multi-scale neighborhood</title><author>NIE JINGMOU ; XIE HE ; LIU XUEBING ; MAO JIANXU ; FENG MINGTAO ; ZHU QING ; WU ZIJIE ; WANG YAONAN</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN114565629A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2022</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>NIE JINGMOU</creatorcontrib><creatorcontrib>XIE HE</creatorcontrib><creatorcontrib>LIU XUEBING</creatorcontrib><creatorcontrib>MAO JIANXU</creatorcontrib><creatorcontrib>FENG MINGTAO</creatorcontrib><creatorcontrib>ZHU QING</creatorcontrib><creatorcontrib>WU ZIJIE</creatorcontrib><creatorcontrib>WANG YAONAN</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>NIE JINGMOU</au><au>XIE HE</au><au>LIU XUEBING</au><au>MAO JIANXU</au><au>FENG MINGTAO</au><au>ZHU QING</au><au>WU ZIJIE</au><au>WANG YAONAN</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Large skin edge defect detection method based on multi-scale neighborhood</title><date>2022-05-31</date><risdate>2022</risdate><abstract>The invention discloses a large skin edge defect detection method based on a multi-scale neighborhood. According to the method, a multi-scale space search method is constructed, space information of corresponding key points is better judged, the search direction is optimized and three-dimensional point cloud edge points are recognized on the basis of the space information, the operation efficiency of three-dimensional image edge recognition is greatly improved, and the recognition success rate is increased; and meanwhile, ordering the extracted boundary points, and detecting defects by using the change of a mask characteristic value. According to the method, edge defect detection of the point cloud image can be more accurately realized in a shorter time, and the method has extremely high algorithm robustness and can be applied to the field of precision detection with large scale, complex structure and high efficiency requirement.
本发明公开了一种基于多尺度邻域的大型蒙皮边缘缺陷检测方法。该方法通过构建一种多尺度空间搜索方法，更好的判断对应关键点的空间信息，并以此为依据优化搜索方向以及识别</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTING COUNTING IMAGE DATA PROCESSING OR GENERATION, IN GENERAL PHYSICS |
| title | Large skin edge defect detection method based on multi-scale neighborhood |
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