• Title/Summary/Keyword: 눈 매스크

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Real Time System Realization for Binocular Eyeball Tracking Mouse (실시간 쌍안구 추적 마우스 시스템 구현에 관한 연구)

  • Ryu Kwang-Ryol;Choi Duck-Hyun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.9
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    • pp.1671-1678
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    • 2006
  • A real time system realization for binocular eyeball tracking mouse on the computer monitor being far from 30-40cm is presented in the paper. The processing for searching eyeball and tracking the cursor are that a facial image is acquired by the small CCD camera, convert it into binary image, search for the eye two using the five region mask method in the eye surroundings and the side four points diagonal positioning method is searched the each iris. The tracking cursor is matched by measuring the iris central moving position. The cursor controlling is achieved by comparing two related distances between the iris maximum moving and the cursor moving to calculate the moving distance from gazing position and screen. The experimental results show that the binocular eyeball mouse system is simple and fast to be real time.

Robust Pupil Detection using Rank Order Filter and Pixel Difference (Rank Order Filter와 화소값 차이를 이용한 강인한 눈동자 검출)

  • Jang, Kyung-Shik
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.7
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    • pp.1383-1390
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    • 2012
  • In this paper, we propose a robust pupil detection method using rank order filter and pixel value difference in facial image. We have detected the potential pupil candidates using rank order filter. Many false pupil candidates found at eyebrow are removed using the fact that the pixel difference is much at the boundary between pupil and sclera. The rest pupil candidates are grouped into pairs. Each pair is verified according to geometric constraints such as the angle and the distance between two candidates. A fitness function is obtained for each pair using the pixel values of two pupil regions, we select a pair with the smallest fitness value as a final pupil. The experiments have been performed for 400 images of the BioID face database. The results show that it achieves more than 90% accuracy, and especially the proposed method improves the detection rate and high accuracy for face with spectacle.