EYE DETECTION BY COMPUTER VISION APPLYING ZERNIKE MOMENTS
Pupil Diameter Measurement
Abstract
Visual impairment is noticed as a conventional problem in many from childbirth. According to the World Health Organization statistics, about one billion people globally have visual impairment. Therefore, Eye tracking technology is considered the most prominent in computer vision and Pattern recognition. Human eye applications have become essential information for streams. The recognition of the Eye patterns is carried out by rotating the pattern at different angles primarily using Gabor Filter and later trained by SVM. The extracted patterns at Lab are transformed and applied with Morphological operations. Every candidate’s Eye pair is detected and classified by using SVM classifier for either eye or non-eye. The Lab and HSV color space use face extraction to find eye pair candidates. Separable Gabor filters decrease computation time and rotation-invariance. The characteristics of the Gabor Filter make the above method robust against rotation. Pupillary changes help in detecting the human eye. Many studies are carried out on pupillary changes to see pupil diameter using samples. Pupil diameter supports the doctor’s decision for early detection of major diseases. A reference algorithm is used for measuring pupil diameter. The proposed approach is tested on rotated images of the GTAV database and capture the videos to obtain maximum result. Zernike moments are used to find refraction errors in Opticians study. They are regularly noticed in adaptive optics to minimize atmospheric pre-compensations.
Keywords
References
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Optimization of interval type-2 fuzzy system using the PSO technique for predictive problems -Dinh Sinh MaiORCIDIcon,Trong Hop
Dang &Long Thanh NgoORCID IconPages 197-213 | Received 27 Apr 2020, Accepted 03 Oct 2020, Published online: 30 Oct 2020.
Real Time Eye Detector with Cascaded Convolutional Neural NetworksBin Li1,2,3and Hong Fu 3 Academic Editor: Erich Peter
KlementReceived 12 Jan 2018 Revised 12 Mar 2018 Accepted 14 Mar 2018 Published 22 Apr 2018
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