{"title":"基于霍夫变换的二维运动估计系统的硬件设计","authors":"Hsiang-Ling Li, C. Chakrabarti","doi":"10.1109/VLSISP.1996.558368","DOIUrl":null,"url":null,"abstract":"A novel feature-domain 2D motion estimation system based on the straight-line Hough transform (SLHT) is presented. This system implements the motion estimation technique proposed by Li and Chakrabarti (see Pattern Recognition, vol.29, no.8, 1996). It operates on 256/spl times/256-pixel binary images and consists of two main blocks. The first block does the preprocessing work including smoothing the boundary, tracing and integrating the contours, and detecting dominant points. The second block computes the Hough transform on contour segments as well as the rotation and translation parameters. Each of the modules has been implemented (gate level) and simulated using Mentor Graphics tools. The experimental results are presented and compared with the results of the software implementation.","PeriodicalId":290885,"journal":{"name":"VLSI Signal Processing, IX","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Hardware design of a Hough transform based 2-D motion estimation system\",\"authors\":\"Hsiang-Ling Li, C. Chakrabarti\",\"doi\":\"10.1109/VLSISP.1996.558368\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A novel feature-domain 2D motion estimation system based on the straight-line Hough transform (SLHT) is presented. This system implements the motion estimation technique proposed by Li and Chakrabarti (see Pattern Recognition, vol.29, no.8, 1996). It operates on 256/spl times/256-pixel binary images and consists of two main blocks. The first block does the preprocessing work including smoothing the boundary, tracing and integrating the contours, and detecting dominant points. The second block computes the Hough transform on contour segments as well as the rotation and translation parameters. Each of the modules has been implemented (gate level) and simulated using Mentor Graphics tools. The experimental results are presented and compared with the results of the software implementation.\",\"PeriodicalId\":290885,\"journal\":{\"name\":\"VLSI Signal Processing, IX\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"VLSI Signal Processing, IX\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VLSISP.1996.558368\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"VLSI Signal Processing, IX","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VLSISP.1996.558368","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hardware design of a Hough transform based 2-D motion estimation system
A novel feature-domain 2D motion estimation system based on the straight-line Hough transform (SLHT) is presented. This system implements the motion estimation technique proposed by Li and Chakrabarti (see Pattern Recognition, vol.29, no.8, 1996). It operates on 256/spl times/256-pixel binary images and consists of two main blocks. The first block does the preprocessing work including smoothing the boundary, tracing and integrating the contours, and detecting dominant points. The second block computes the Hough transform on contour segments as well as the rotation and translation parameters. Each of the modules has been implemented (gate level) and simulated using Mentor Graphics tools. The experimental results are presented and compared with the results of the software implementation.