Javad Rahebi, Z. Elmi, Ali Farzam nia, Kamran Shayan
{"title":"基于蚁群优化遗传算法的数字图像边缘检测","authors":"Javad Rahebi, Z. Elmi, Ali Farzam nia, Kamran Shayan","doi":"10.1109/ICCIS.2010.5518567","DOIUrl":null,"url":null,"abstract":"In this paper a new method for enhancement of digital image edge detection using ant colony optimization based on genetic algorithm has been used. In the proposed method first by the series of answers has been formed by artificial ants and then formed in a manner i.e. useful for genetic algorithm, then the answers played the role as initial population for genetic algorithm and the next population is made by genetic algorithm. Our method compared with Jing Tian method enjoys higher speed, less processing time and more answer's optimum. Also the proposed method has a better edge than other classical methods (such as sobel, etc).","PeriodicalId":445473,"journal":{"name":"2010 IEEE Conference on Cybernetics and Intelligent Systems","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":"{\"title\":\"Digital image edge detection using an ant colony optimization based on genetic algorithm\",\"authors\":\"Javad Rahebi, Z. Elmi, Ali Farzam nia, Kamran Shayan\",\"doi\":\"10.1109/ICCIS.2010.5518567\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper a new method for enhancement of digital image edge detection using ant colony optimization based on genetic algorithm has been used. In the proposed method first by the series of answers has been formed by artificial ants and then formed in a manner i.e. useful for genetic algorithm, then the answers played the role as initial population for genetic algorithm and the next population is made by genetic algorithm. Our method compared with Jing Tian method enjoys higher speed, less processing time and more answer's optimum. Also the proposed method has a better edge than other classical methods (such as sobel, etc).\",\"PeriodicalId\":445473,\"journal\":{\"name\":\"2010 IEEE Conference on Cybernetics and Intelligent Systems\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"22\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE Conference on Cybernetics and Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIS.2010.5518567\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE Conference on Cybernetics and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIS.2010.5518567","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Digital image edge detection using an ant colony optimization based on genetic algorithm
In this paper a new method for enhancement of digital image edge detection using ant colony optimization based on genetic algorithm has been used. In the proposed method first by the series of answers has been formed by artificial ants and then formed in a manner i.e. useful for genetic algorithm, then the answers played the role as initial population for genetic algorithm and the next population is made by genetic algorithm. Our method compared with Jing Tian method enjoys higher speed, less processing time and more answer's optimum. Also the proposed method has a better edge than other classical methods (such as sobel, etc).
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
