T. Charoenpong, S. Thewsuwan, Theerasak Chanwimalueang, V. Mahasithiwat
{"title":"基于k均值聚类和马氏距离技术的眼球震颤诊断瞳孔提取系统","authors":"T. Charoenpong, S. Thewsuwan, Theerasak Chanwimalueang, V. Mahasithiwat","doi":"10.1109/KST.2012.6287735","DOIUrl":null,"url":null,"abstract":"As vertigo is a type of dizziness, it causes by problem with nystagmus. Doctors can diagnosis this disease from observing the motion of inner eye. For Nystagmus diagnosis system, efficient and precise pupil extraction system is needed. This paper proposed a method of pupil extraction by using K-mean clustering and Mahalanobis distance. Image sequence is captured via infrared camera mounted on the binocular. Eye tracking algorithm is consisted of K-mean clustering and Mahalanobis Distance. Based on the darkness of pupil, K-means clustering algorithm is used to segment black pixels. Extracted region is pupil, however noise is occurred. The noisy data is eliminated by means of Mahalanobis distance technique. Then the pupil is extracted. For experimental result, 1869 frames from 9 image sequences are use to test the performance of the proposed method. Accuracy is 73.68%, precision is 3.18 pixels error.","PeriodicalId":209504,"journal":{"name":"Knowledge and Smart Technology (KST)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Pupil extraction system for Nystagmus diagnosis by using K-mean clustering and Mahalanobis distance technique\",\"authors\":\"T. Charoenpong, S. Thewsuwan, Theerasak Chanwimalueang, V. Mahasithiwat\",\"doi\":\"10.1109/KST.2012.6287735\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As vertigo is a type of dizziness, it causes by problem with nystagmus. Doctors can diagnosis this disease from observing the motion of inner eye. For Nystagmus diagnosis system, efficient and precise pupil extraction system is needed. This paper proposed a method of pupil extraction by using K-mean clustering and Mahalanobis distance. Image sequence is captured via infrared camera mounted on the binocular. Eye tracking algorithm is consisted of K-mean clustering and Mahalanobis Distance. Based on the darkness of pupil, K-means clustering algorithm is used to segment black pixels. Extracted region is pupil, however noise is occurred. The noisy data is eliminated by means of Mahalanobis distance technique. Then the pupil is extracted. For experimental result, 1869 frames from 9 image sequences are use to test the performance of the proposed method. Accuracy is 73.68%, precision is 3.18 pixels error.\",\"PeriodicalId\":209504,\"journal\":{\"name\":\"Knowledge and Smart Technology (KST)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-07-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Knowledge and Smart Technology (KST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/KST.2012.6287735\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Knowledge and Smart Technology (KST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/KST.2012.6287735","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pupil extraction system for Nystagmus diagnosis by using K-mean clustering and Mahalanobis distance technique
As vertigo is a type of dizziness, it causes by problem with nystagmus. Doctors can diagnosis this disease from observing the motion of inner eye. For Nystagmus diagnosis system, efficient and precise pupil extraction system is needed. This paper proposed a method of pupil extraction by using K-mean clustering and Mahalanobis distance. Image sequence is captured via infrared camera mounted on the binocular. Eye tracking algorithm is consisted of K-mean clustering and Mahalanobis Distance. Based on the darkness of pupil, K-means clustering algorithm is used to segment black pixels. Extracted region is pupil, however noise is occurred. The noisy data is eliminated by means of Mahalanobis distance technique. Then the pupil is extracted. For experimental result, 1869 frames from 9 image sequences are use to test the performance of the proposed method. Accuracy is 73.68%, precision is 3.18 pixels error.