{"title":"基于MRF和模糊聚类的甲骨文字图像分割新方法","authors":"Xiaoju He, Zhiwu Liao","doi":"10.1109/SPAC.2017.8304276","DOIUrl":null,"url":null,"abstract":"JiaGuWen image segmentation is a challenge because of their illegible writing, serious noises and broken strokes. We propose a new segmentation method based on MRF and fuzzy clustering because of their good performance in image segmentation. The segmentation is based on a new random function considering both ambiguity and spatial relationship of image pieds simultaneously. The New adaptive balance coefficient is computed according to the gray level of the considering pixel and the mean, standard deviation of the neighbor. The final value of the new random function is searching by iteration. The experiments show that the new method has good performance for JiaGuWen image segmentation.","PeriodicalId":318775,"journal":{"name":"International Conference on Security, Pattern Analysis, and Cybernetics","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"New method for jiaguwen image segmentation based on MRF and fuzzy clustering\",\"authors\":\"Xiaoju He, Zhiwu Liao\",\"doi\":\"10.1109/SPAC.2017.8304276\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"JiaGuWen image segmentation is a challenge because of their illegible writing, serious noises and broken strokes. We propose a new segmentation method based on MRF and fuzzy clustering because of their good performance in image segmentation. The segmentation is based on a new random function considering both ambiguity and spatial relationship of image pieds simultaneously. The New adaptive balance coefficient is computed according to the gray level of the considering pixel and the mean, standard deviation of the neighbor. The final value of the new random function is searching by iteration. The experiments show that the new method has good performance for JiaGuWen image segmentation.\",\"PeriodicalId\":318775,\"journal\":{\"name\":\"International Conference on Security, Pattern Analysis, and Cybernetics\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Security, Pattern Analysis, and Cybernetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPAC.2017.8304276\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Security, Pattern Analysis, and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPAC.2017.8304276","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
New method for jiaguwen image segmentation based on MRF and fuzzy clustering
JiaGuWen image segmentation is a challenge because of their illegible writing, serious noises and broken strokes. We propose a new segmentation method based on MRF and fuzzy clustering because of their good performance in image segmentation. The segmentation is based on a new random function considering both ambiguity and spatial relationship of image pieds simultaneously. The New adaptive balance coefficient is computed according to the gray level of the considering pixel and the mean, standard deviation of the neighbor. The final value of the new random function is searching by iteration. The experiments show that the new method has good performance for JiaGuWen image segmentation.