{"title":"一种改进的指纹图像分割方法","authors":"Rojas Vda, S.J.L. Aching","doi":"10.1109/CERMA.2006.12","DOIUrl":null,"url":null,"abstract":"In this work, an improved method for the pixel-wise segmentation technique is presented. Three features are extracted from each pixel and a linear classifier associates the pixel with the background or the foreground. Since this technique requires a trade-off between the accuracy of the classification and the computational effort, we propose a modified editing-condensing technique to select a reduced and representative reference set from the original training set. Also, because this is a linearly nonseparable classification problem, we propose the fuzzy perceptron learning method to obtain an optimal and robust lineal classifier. Experiments have shown that using the proposed method a reduced number of epochs and classification errors were obtained","PeriodicalId":179210,"journal":{"name":"Electronics, Robotics and Automotive Mechanics Conference (CERMA'06)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"An Improved Method for Segmentation of Fingerprint Images\",\"authors\":\"Rojas Vda, S.J.L. Aching\",\"doi\":\"10.1109/CERMA.2006.12\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work, an improved method for the pixel-wise segmentation technique is presented. Three features are extracted from each pixel and a linear classifier associates the pixel with the background or the foreground. Since this technique requires a trade-off between the accuracy of the classification and the computational effort, we propose a modified editing-condensing technique to select a reduced and representative reference set from the original training set. Also, because this is a linearly nonseparable classification problem, we propose the fuzzy perceptron learning method to obtain an optimal and robust lineal classifier. Experiments have shown that using the proposed method a reduced number of epochs and classification errors were obtained\",\"PeriodicalId\":179210,\"journal\":{\"name\":\"Electronics, Robotics and Automotive Mechanics Conference (CERMA'06)\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Electronics, Robotics and Automotive Mechanics Conference (CERMA'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CERMA.2006.12\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electronics, Robotics and Automotive Mechanics Conference (CERMA'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CERMA.2006.12","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Improved Method for Segmentation of Fingerprint Images
In this work, an improved method for the pixel-wise segmentation technique is presented. Three features are extracted from each pixel and a linear classifier associates the pixel with the background or the foreground. Since this technique requires a trade-off between the accuracy of the classification and the computational effort, we propose a modified editing-condensing technique to select a reduced and representative reference set from the original training set. Also, because this is a linearly nonseparable classification problem, we propose the fuzzy perceptron learning method to obtain an optimal and robust lineal classifier. Experiments have shown that using the proposed method a reduced number of epochs and classification errors were obtained