{"title":"基于群体智能的图像阈值分割技术","authors":"Shivali, Ekta Sharma, P. Mahapatra, Amit Doegar","doi":"10.1109/INCITE.2016.7857626","DOIUrl":null,"url":null,"abstract":"Image thresholding is a critical task of image segmentation. Selection of the optimal value of the threshold is the most important task for image thresholding. The better the value of threshold better is the quality of segmentation. In this paper, recent swarm intelligence technique (fireworks algorithm) has been used for image thresholding. Fireworks algorithm is used to maximize two functions, namely Kapur and Otsu. Results show that quality of segmentation is better in case of Firewok-Otsu than Firework-Kapur. Comparison of results has been done on the basis of PSNR value.","PeriodicalId":59618,"journal":{"name":"下一代","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Image thresholding based on swarm intelligence technique for image segmentation\",\"authors\":\"Shivali, Ekta Sharma, P. Mahapatra, Amit Doegar\",\"doi\":\"10.1109/INCITE.2016.7857626\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Image thresholding is a critical task of image segmentation. Selection of the optimal value of the threshold is the most important task for image thresholding. The better the value of threshold better is the quality of segmentation. In this paper, recent swarm intelligence technique (fireworks algorithm) has been used for image thresholding. Fireworks algorithm is used to maximize two functions, namely Kapur and Otsu. Results show that quality of segmentation is better in case of Firewok-Otsu than Firework-Kapur. Comparison of results has been done on the basis of PSNR value.\",\"PeriodicalId\":59618,\"journal\":{\"name\":\"下一代\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"下一代\",\"FirstCategoryId\":\"1092\",\"ListUrlMain\":\"https://doi.org/10.1109/INCITE.2016.7857626\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"下一代","FirstCategoryId":"1092","ListUrlMain":"https://doi.org/10.1109/INCITE.2016.7857626","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Image thresholding based on swarm intelligence technique for image segmentation
Image thresholding is a critical task of image segmentation. Selection of the optimal value of the threshold is the most important task for image thresholding. The better the value of threshold better is the quality of segmentation. In this paper, recent swarm intelligence technique (fireworks algorithm) has been used for image thresholding. Fireworks algorithm is used to maximize two functions, namely Kapur and Otsu. Results show that quality of segmentation is better in case of Firewok-Otsu than Firework-Kapur. Comparison of results has been done on the basis of PSNR value.
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