{"title":"基于萤火虫算法的多级阈值图像分割","authors":"M. Sridevi","doi":"10.1109/ICICI.2017.8365235","DOIUrl":null,"url":null,"abstract":"Image segmentation involves identifying the distinct objects present in an image based on the properties such as intensity, color, texture etc. There are many image segmentation techniques namely, edge, threshold and region based developed since the past three decades. Thresholding is one such technique which generates a number of threshold values, which can be used to segment the image. Determining the optimal number of thresholds and their values is still a challenging problem. A method using firefly algorithm an optimization technique is proposed in this paper to determine the optimal threshold number and values for performing segmentation process. From the experimental results, it is inferred that the proposed method provides better segmented image.","PeriodicalId":369524,"journal":{"name":"2017 International Conference on Inventive Computing and Informatics (ICICI)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Image segmentation based on multilevel thresholding using firefly algorithm\",\"authors\":\"M. Sridevi\",\"doi\":\"10.1109/ICICI.2017.8365235\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Image segmentation involves identifying the distinct objects present in an image based on the properties such as intensity, color, texture etc. There are many image segmentation techniques namely, edge, threshold and region based developed since the past three decades. Thresholding is one such technique which generates a number of threshold values, which can be used to segment the image. Determining the optimal number of thresholds and their values is still a challenging problem. A method using firefly algorithm an optimization technique is proposed in this paper to determine the optimal threshold number and values for performing segmentation process. From the experimental results, it is inferred that the proposed method provides better segmented image.\",\"PeriodicalId\":369524,\"journal\":{\"name\":\"2017 International Conference on Inventive Computing and Informatics (ICICI)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Inventive Computing and Informatics (ICICI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICI.2017.8365235\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Inventive Computing and Informatics (ICICI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICI.2017.8365235","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Image segmentation based on multilevel thresholding using firefly algorithm
Image segmentation involves identifying the distinct objects present in an image based on the properties such as intensity, color, texture etc. There are many image segmentation techniques namely, edge, threshold and region based developed since the past three decades. Thresholding is one such technique which generates a number of threshold values, which can be used to segment the image. Determining the optimal number of thresholds and their values is still a challenging problem. A method using firefly algorithm an optimization technique is proposed in this paper to determine the optimal threshold number and values for performing segmentation process. From the experimental results, it is inferred that the proposed method provides better segmented image.