{"title":"基于动态阈值的精子视频分割","authors":"Z. Xuan, Wang Yan","doi":"10.1109/ICMLC.2010.5580766","DOIUrl":null,"url":null,"abstract":"In this paper, the method of threshold segmentation is introduced, which focus on the image characteristics of the sperm video, base on the dynamic threshold and combine with region growing arithmetic. The method is based on the movement characteristics and the brightness characteristics of the objective sperm to distinct, and then uses the region growing algorithm to calculate the sperm region, finally according to this gray area to determine the threshold. The results show that this method has better performance to divide the sperm goal.","PeriodicalId":126080,"journal":{"name":"2010 International Conference on Machine Learning and Cybernetics","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"The sperm video segmentation based on dynamic threshold\",\"authors\":\"Z. Xuan, Wang Yan\",\"doi\":\"10.1109/ICMLC.2010.5580766\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, the method of threshold segmentation is introduced, which focus on the image characteristics of the sperm video, base on the dynamic threshold and combine with region growing arithmetic. The method is based on the movement characteristics and the brightness characteristics of the objective sperm to distinct, and then uses the region growing algorithm to calculate the sperm region, finally according to this gray area to determine the threshold. The results show that this method has better performance to divide the sperm goal.\",\"PeriodicalId\":126080,\"journal\":{\"name\":\"2010 International Conference on Machine Learning and Cybernetics\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-07-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Machine Learning and Cybernetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMLC.2010.5580766\",\"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 International Conference on Machine Learning and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMLC.2010.5580766","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The sperm video segmentation based on dynamic threshold
In this paper, the method of threshold segmentation is introduced, which focus on the image characteristics of the sperm video, base on the dynamic threshold and combine with region growing arithmetic. The method is based on the movement characteristics and the brightness characteristics of the objective sperm to distinct, and then uses the region growing algorithm to calculate the sperm region, finally according to this gray area to determine the threshold. The results show that this method has better performance to divide the sperm goal.
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