{"title":"基于改进Sobel算子和遗传算法的图像边缘检测","authors":"Zhang Jin-Yu, Chengxin Yan, Huang Xian-xiang","doi":"10.1109/IASP.2009.5054605","DOIUrl":null,"url":null,"abstract":"Edge detection of images is a classical problem in computer vision and image processing. The key of edge detection is the choice of threshold; the choice of threshold directly determines the results of edge detection. How to automatically determine an optimal threshold is one of difficult points of edge detection. In this paper, Sobel edge detection operator and its improved algorithm are first discussed in term of optimal thresholding. Then based on Genetic Algorithms and improved Sobel operator, a new automatic threshold algorithm for images processing is proposed. Finally, the edge detection experiments of two real images are conducted by means of two algorithms. The comparative experiment results show that the new algorithm of automatic threshold is very effective. The results are also better than the classical Otsu methods.","PeriodicalId":143959,"journal":{"name":"2009 International Conference on Image Analysis and Signal Processing","volume":"41 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"152","resultStr":"{\"title\":\"Edge detection of images based on improved Sobel operator and genetic algorithms\",\"authors\":\"Zhang Jin-Yu, Chengxin Yan, Huang Xian-xiang\",\"doi\":\"10.1109/IASP.2009.5054605\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Edge detection of images is a classical problem in computer vision and image processing. The key of edge detection is the choice of threshold; the choice of threshold directly determines the results of edge detection. How to automatically determine an optimal threshold is one of difficult points of edge detection. In this paper, Sobel edge detection operator and its improved algorithm are first discussed in term of optimal thresholding. Then based on Genetic Algorithms and improved Sobel operator, a new automatic threshold algorithm for images processing is proposed. Finally, the edge detection experiments of two real images are conducted by means of two algorithms. The comparative experiment results show that the new algorithm of automatic threshold is very effective. The results are also better than the classical Otsu methods.\",\"PeriodicalId\":143959,\"journal\":{\"name\":\"2009 International Conference on Image Analysis and Signal Processing\",\"volume\":\"41 2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-04-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"152\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Image Analysis and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IASP.2009.5054605\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Image Analysis and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IASP.2009.5054605","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Edge detection of images based on improved Sobel operator and genetic algorithms
Edge detection of images is a classical problem in computer vision and image processing. The key of edge detection is the choice of threshold; the choice of threshold directly determines the results of edge detection. How to automatically determine an optimal threshold is one of difficult points of edge detection. In this paper, Sobel edge detection operator and its improved algorithm are first discussed in term of optimal thresholding. Then based on Genetic Algorithms and improved Sobel operator, a new automatic threshold algorithm for images processing is proposed. Finally, the edge detection experiments of two real images are conducted by means of two algorithms. The comparative experiment results show that the new algorithm of automatic threshold is very effective. The results are also better than the classical Otsu methods.