Weixing Zhu, Changhua Ma, Libing Xia, Xin-cheng Li
{"title":"一种快速准确的棋盘角点检测算法","authors":"Weixing Zhu, Changhua Ma, Libing Xia, Xin-cheng Li","doi":"10.1109/CISP.2009.5304332","DOIUrl":null,"url":null,"abstract":"The authors point out the limitations of SUSAN corner detector in detecting chessboard corner, then describe an improved SUSAN(Smallest Univalue Segment Assimilating Nucleus) detector algorithm for detecting chessboard corner on the basis of symmetrical geometry structure of USAN (Univalue Segment Assimilating Nucleus) area. And the algorithm has been applied to the chessboard images on real photos. The improved algorithm can quickly detect corner from real photos shot from every angle. The theory of detecting corner at sub-pixel level is Orthogonal Vector Theory, that is, vector from the corner to its adjacent area pixel point should be vertical to gray grads of the adjacent area pixel point. In order to get the coordinate of corner at sub-pixel level, we establish the neighboring area equation and solve it via iterative method, and propose to check its validity according to cross ratio invariability in perspective projection. Keywords-insert chessboard corner; USAN; sub-pixel; cross ratio invariability","PeriodicalId":263281,"journal":{"name":"2009 2nd International Congress on Image and Signal Processing","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"29","resultStr":"{\"title\":\"A Fast and Accurate Algorithm for Chessboard Corner Detection\",\"authors\":\"Weixing Zhu, Changhua Ma, Libing Xia, Xin-cheng Li\",\"doi\":\"10.1109/CISP.2009.5304332\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The authors point out the limitations of SUSAN corner detector in detecting chessboard corner, then describe an improved SUSAN(Smallest Univalue Segment Assimilating Nucleus) detector algorithm for detecting chessboard corner on the basis of symmetrical geometry structure of USAN (Univalue Segment Assimilating Nucleus) area. And the algorithm has been applied to the chessboard images on real photos. The improved algorithm can quickly detect corner from real photos shot from every angle. The theory of detecting corner at sub-pixel level is Orthogonal Vector Theory, that is, vector from the corner to its adjacent area pixel point should be vertical to gray grads of the adjacent area pixel point. In order to get the coordinate of corner at sub-pixel level, we establish the neighboring area equation and solve it via iterative method, and propose to check its validity according to cross ratio invariability in perspective projection. Keywords-insert chessboard corner; USAN; sub-pixel; cross ratio invariability\",\"PeriodicalId\":263281,\"journal\":{\"name\":\"2009 2nd International Congress on Image and Signal Processing\",\"volume\":\"67 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"29\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 2nd International Congress on Image and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CISP.2009.5304332\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 2nd International Congress on Image and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP.2009.5304332","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Fast and Accurate Algorithm for Chessboard Corner Detection
The authors point out the limitations of SUSAN corner detector in detecting chessboard corner, then describe an improved SUSAN(Smallest Univalue Segment Assimilating Nucleus) detector algorithm for detecting chessboard corner on the basis of symmetrical geometry structure of USAN (Univalue Segment Assimilating Nucleus) area. And the algorithm has been applied to the chessboard images on real photos. The improved algorithm can quickly detect corner from real photos shot from every angle. The theory of detecting corner at sub-pixel level is Orthogonal Vector Theory, that is, vector from the corner to its adjacent area pixel point should be vertical to gray grads of the adjacent area pixel point. In order to get the coordinate of corner at sub-pixel level, we establish the neighboring area equation and solve it via iterative method, and propose to check its validity according to cross ratio invariability in perspective projection. Keywords-insert chessboard corner; USAN; sub-pixel; cross ratio invariability