{"title":"基于金字塔结构的层次霍夫变换","authors":"C. Espinosa, M. Perkowski","doi":"10.1109/PCCC.1992.200515","DOIUrl":null,"url":null,"abstract":"A hierarchical Hough transform (HT) based on pyramidal architecture is described, being a main component of the low-to-medium spatial vision subsystem for a mobile robot. The sequence of processing in the system originally conceived to be essential to the extraction of line features in indoor scenes consisted of: histogram equalization, smoothing with the use of a medial filter, edge detection using the Sobel edge detectors, binarization to extract the edges detected, labeling, rebinarization and thinning to refine the edges to thin lines, and line extraction using a hierarchical approach to the HT method. The task was to establish the importance of each step for the success of the hierarchical HT. It was implemented on a 386-based personal computer with 640 K memory and proved to give results of high quality as compared with the standard HT implementation.<<ETX>>","PeriodicalId":250212,"journal":{"name":"Eleventh Annual International Phoenix Conference on Computers and Communication [1992 Conference Proceedings]","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Hierarchical Hough transform based on pyramidal architecture\",\"authors\":\"C. Espinosa, M. Perkowski\",\"doi\":\"10.1109/PCCC.1992.200515\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A hierarchical Hough transform (HT) based on pyramidal architecture is described, being a main component of the low-to-medium spatial vision subsystem for a mobile robot. The sequence of processing in the system originally conceived to be essential to the extraction of line features in indoor scenes consisted of: histogram equalization, smoothing with the use of a medial filter, edge detection using the Sobel edge detectors, binarization to extract the edges detected, labeling, rebinarization and thinning to refine the edges to thin lines, and line extraction using a hierarchical approach to the HT method. The task was to establish the importance of each step for the success of the hierarchical HT. It was implemented on a 386-based personal computer with 640 K memory and proved to give results of high quality as compared with the standard HT implementation.<<ETX>>\",\"PeriodicalId\":250212,\"journal\":{\"name\":\"Eleventh Annual International Phoenix Conference on Computers and Communication [1992 Conference Proceedings]\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Eleventh Annual International Phoenix Conference on Computers and Communication [1992 Conference Proceedings]\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PCCC.1992.200515\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Eleventh Annual International Phoenix Conference on Computers and Communication [1992 Conference Proceedings]","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PCCC.1992.200515","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hierarchical Hough transform based on pyramidal architecture
A hierarchical Hough transform (HT) based on pyramidal architecture is described, being a main component of the low-to-medium spatial vision subsystem for a mobile robot. The sequence of processing in the system originally conceived to be essential to the extraction of line features in indoor scenes consisted of: histogram equalization, smoothing with the use of a medial filter, edge detection using the Sobel edge detectors, binarization to extract the edges detected, labeling, rebinarization and thinning to refine the edges to thin lines, and line extraction using a hierarchical approach to the HT method. The task was to establish the importance of each step for the success of the hierarchical HT. It was implemented on a 386-based personal computer with 640 K memory and proved to give results of high quality as compared with the standard HT implementation.<>