Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/14258
ชื่อเรื่อง: Pupil extraction system for Nystagmus diagnosis by using K-mean clustering and Mahalanobis distance technique
ผู้แต่ง: Charoenpong T.
Thewsuwan S.
Chanwimalueang T.
Mahasithiwat V.
Keywords: Black pixels
Diagnosis systems
Extraction systems
Eye-tracking
Image sequence
Infra-red cameras
K-mean clustering
K-Means clustering algorithm
Mahalanobis distances
Noisy data
Clustering algorithms
Eye movements
Occupational diseases
Pixels
Technology
Diagnosis
วันที่เผยแพร่: 2012
บทคัดย่อ: 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. © 2012 IEEE.
URI: https://ir.swu.ac.th/jspui/handle/123456789/14258
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84867717719&doi=10.1109%2fKST.2012.6287735&partnerID=40&md5=9cf1b1151860148689f4e8d2ae2e39d9
Appears in Collections:Scopus 1983-2021

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