Real Time Squint Eye Detection
R. M. Potdar1, Anil Mishra2, Somesh Yadav3
1M. Potdar , Sr. Associate Professor ,Department of Electronics & Telecommunication Engineering, Bhilai Institute of Technology (BIT), Durg , Chhattisgarh, India.
2Anil Mishra , Associate Professor ,Department of Electronics & Telecommunication Engineering, Bhilai Institute of Technology (BIT), Durg , Chhattisgarh, India.
3Somesh Yadav , Assistant Professor ,Department of Electrical & Electronics Engineering, Chhatrapati Shivaji Institute of Technology (CSIT), Durg, Chhattisgarh, India.
Manuscript received on November 01, 2011. | Revised Manuscript received on December 12, 2011. | Manuscript published on December 30, 2011. | PP: 111-114 | Volume-1 Issue-2, December 2011. | Retrieval Number: B0158121211/2011©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper provides a survey on Real Time Squint Eye Detection. This is due to defective binocular vision which causes Vision loss in the turned eye. The eyes need to be straight for the brain to combine the images seen by the two eyes into a single picture. This gives us 3-D vision, which allows us to judge depth. Any turn of the eye can interrupt 3-D vision, if an eye turns in, it can reduce the total field of vision. Over the years, many methodologies have been developed to detect squint eye. In this paper, we have proposed an overview on squint eye detection system and their classification with some drawback and basic assumption for squint eye detection.
Keywords: Hough transform, image Processing, modelling, projection function, segmentation.