{"title":"结合几何和光度信息,从步进边缘检测找到线","authors":"Alain Filbois","doi":"10.1109/TAI.1994.346396","DOIUrl":null,"url":null,"abstract":"This paper deals with the problem of detecting both step and line edges using a classical step edge detector. As a gradient detector produces two extrema when applied to a line, we propose a method which is based on such a detector but which appropriately responds to both step and line edges. The idea is first to identify line contours using geometric and photometric properties and second to substitute a line for a single contour using a skeletonization algorithm.<<ETX>>","PeriodicalId":262014,"journal":{"name":"Proceedings Sixth International Conference on Tools with Artificial Intelligence. TAI 94","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Combining geometric and photometric information to find lines from step edge detection\",\"authors\":\"Alain Filbois\",\"doi\":\"10.1109/TAI.1994.346396\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper deals with the problem of detecting both step and line edges using a classical step edge detector. As a gradient detector produces two extrema when applied to a line, we propose a method which is based on such a detector but which appropriately responds to both step and line edges. The idea is first to identify line contours using geometric and photometric properties and second to substitute a line for a single contour using a skeletonization algorithm.<<ETX>>\",\"PeriodicalId\":262014,\"journal\":{\"name\":\"Proceedings Sixth International Conference on Tools with Artificial Intelligence. TAI 94\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings Sixth International Conference on Tools with Artificial Intelligence. TAI 94\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TAI.1994.346396\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Sixth International Conference on Tools with Artificial Intelligence. TAI 94","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TAI.1994.346396","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Combining geometric and photometric information to find lines from step edge detection
This paper deals with the problem of detecting both step and line edges using a classical step edge detector. As a gradient detector produces two extrema when applied to a line, we propose a method which is based on such a detector but which appropriately responds to both step and line edges. The idea is first to identify line contours using geometric and photometric properties and second to substitute a line for a single contour using a skeletonization algorithm.<>