{"title":"染色体图像的边缘检测方法","authors":"Yan Wenzhong, Shen Shuqun","doi":"10.1109/ICBBE.2008.930","DOIUrl":null,"url":null,"abstract":"Edge detection for chromosome images is an important step in automated chromosome analysis system. The key of edge detection for chromosome image is to detect more edge details, reduce the noise impact to the largest degree. According to this, an edge detection method based on iterative thresholding and mathematic morphology is proposed in this paper. Firstly, the iterative thresholding algorithm is applied to enhance both the edges of the chromosomes and the contrast of the image. Then, the contour extracting algorithm is applied to detect the edges of the chromosomes in the image. The experimental results show that the proposed algorithm is more efficient for chromosome image edge detection than the usually used differential operators.","PeriodicalId":6399,"journal":{"name":"2008 2nd International Conference on Bioinformatics and Biomedical Engineering","volume":"22 1","pages":"2390-2392"},"PeriodicalIF":0.0000,"publicationDate":"2008-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"An Edge Detection Method for Chromosome Images\",\"authors\":\"Yan Wenzhong, Shen Shuqun\",\"doi\":\"10.1109/ICBBE.2008.930\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Edge detection for chromosome images is an important step in automated chromosome analysis system. The key of edge detection for chromosome image is to detect more edge details, reduce the noise impact to the largest degree. According to this, an edge detection method based on iterative thresholding and mathematic morphology is proposed in this paper. Firstly, the iterative thresholding algorithm is applied to enhance both the edges of the chromosomes and the contrast of the image. Then, the contour extracting algorithm is applied to detect the edges of the chromosomes in the image. The experimental results show that the proposed algorithm is more efficient for chromosome image edge detection than the usually used differential operators.\",\"PeriodicalId\":6399,\"journal\":{\"name\":\"2008 2nd International Conference on Bioinformatics and Biomedical Engineering\",\"volume\":\"22 1\",\"pages\":\"2390-2392\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 2nd International Conference on Bioinformatics and Biomedical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICBBE.2008.930\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 2nd International Conference on Bioinformatics and Biomedical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICBBE.2008.930","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Edge detection for chromosome images is an important step in automated chromosome analysis system. The key of edge detection for chromosome image is to detect more edge details, reduce the noise impact to the largest degree. According to this, an edge detection method based on iterative thresholding and mathematic morphology is proposed in this paper. Firstly, the iterative thresholding algorithm is applied to enhance both the edges of the chromosomes and the contrast of the image. Then, the contour extracting algorithm is applied to detect the edges of the chromosomes in the image. The experimental results show that the proposed algorithm is more efficient for chromosome image edge detection than the usually used differential operators.