Luisa F. Ramirez, A. F. Gutiérrez, J. L. Ocampo, C. Madrigal, J. Branch, A. Restrepo
{"title":"利用结构光进行三维重建,提取彩色编码模式的对应关系","authors":"Luisa F. Ramirez, A. F. Gutiérrez, J. L. Ocampo, C. Madrigal, J. Branch, A. Restrepo","doi":"10.1109/STSIVA.2014.7010164","DOIUrl":null,"url":null,"abstract":"This paper presents a methodology to extract correspondences on images of color patterns based on the De Bruijn sequence projected on static objects and surfaces with no specular highlights, decreasing in great number the problems with occlusions which appear with this pattern. The methodology aims to capture and process the image, the detection of changes in intensity between stripes of the pattern for each color channel R, G, B, a selective contextual algorithm and finally the comparison of neighbors to determine the similar regions. Experimental tests demonstrate that the proposed methodology identifies large number of correspondences in the images with a low error rate.","PeriodicalId":114554,"journal":{"name":"2014 XIX Symposium on Image, Signal Processing and Artificial Vision","volume":"54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Extraction of correspondences in color coded pattern for the 3D reconstruction using structured light\",\"authors\":\"Luisa F. Ramirez, A. F. Gutiérrez, J. L. Ocampo, C. Madrigal, J. Branch, A. Restrepo\",\"doi\":\"10.1109/STSIVA.2014.7010164\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a methodology to extract correspondences on images of color patterns based on the De Bruijn sequence projected on static objects and surfaces with no specular highlights, decreasing in great number the problems with occlusions which appear with this pattern. The methodology aims to capture and process the image, the detection of changes in intensity between stripes of the pattern for each color channel R, G, B, a selective contextual algorithm and finally the comparison of neighbors to determine the similar regions. Experimental tests demonstrate that the proposed methodology identifies large number of correspondences in the images with a low error rate.\",\"PeriodicalId\":114554,\"journal\":{\"name\":\"2014 XIX Symposium on Image, Signal Processing and Artificial Vision\",\"volume\":\"54 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 XIX Symposium on Image, Signal Processing and Artificial Vision\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/STSIVA.2014.7010164\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 XIX Symposium on Image, Signal Processing and Artificial Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/STSIVA.2014.7010164","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Extraction of correspondences in color coded pattern for the 3D reconstruction using structured light
This paper presents a methodology to extract correspondences on images of color patterns based on the De Bruijn sequence projected on static objects and surfaces with no specular highlights, decreasing in great number the problems with occlusions which appear with this pattern. The methodology aims to capture and process the image, the detection of changes in intensity between stripes of the pattern for each color channel R, G, B, a selective contextual algorithm and finally the comparison of neighbors to determine the similar regions. Experimental tests demonstrate that the proposed methodology identifies large number of correspondences in the images with a low error rate.