{"title":"同步多处理器实现的霍夫变换","authors":"D Ben-Tzvi, A Naqvi, M Sandler","doi":"10.1016/0734-189X(90)90086-B","DOIUrl":null,"url":null,"abstract":"<div><p>Normally, in parallel implementations of the Hough transform either the transform space or the set of image features can be distributed among the processing elements. A method is proposed to link parallel access to feature points in the image, and parallel access to the transform space. A synchronous processing sequence is suggested such that both can be distributed. Real-time performance has been obtained on a MIMD distributed memory architecture.</p></div>","PeriodicalId":100319,"journal":{"name":"Computer Vision, Graphics, and Image Processing","volume":"52 3","pages":"Pages 437-446"},"PeriodicalIF":0.0000,"publicationDate":"1990-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0734-189X(90)90086-B","citationCount":"26","resultStr":"{\"title\":\"Synchronous multiprocessor implementation of the Hough transform\",\"authors\":\"D Ben-Tzvi, A Naqvi, M Sandler\",\"doi\":\"10.1016/0734-189X(90)90086-B\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Normally, in parallel implementations of the Hough transform either the transform space or the set of image features can be distributed among the processing elements. A method is proposed to link parallel access to feature points in the image, and parallel access to the transform space. A synchronous processing sequence is suggested such that both can be distributed. Real-time performance has been obtained on a MIMD distributed memory architecture.</p></div>\",\"PeriodicalId\":100319,\"journal\":{\"name\":\"Computer Vision, Graphics, and Image Processing\",\"volume\":\"52 3\",\"pages\":\"Pages 437-446\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1990-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/0734-189X(90)90086-B\",\"citationCount\":\"26\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer Vision, Graphics, and Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/0734189X9090086B\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Vision, Graphics, and Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/0734189X9090086B","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Synchronous multiprocessor implementation of the Hough transform
Normally, in parallel implementations of the Hough transform either the transform space or the set of image features can be distributed among the processing elements. A method is proposed to link parallel access to feature points in the image, and parallel access to the transform space. A synchronous processing sequence is suggested such that both can be distributed. Real-time performance has been obtained on a MIMD distributed memory architecture.
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