Loading

Sclera Segmentation techniques
Swechchha Sharma1, Gokul Rajan V2

1Gokul Rajan V*, Assistant Professor, School of Computing Science and Engineering, Galgotias University, Greater Noida, India.
2Swechchha Sharma, Student, Department of Computer Science and Engineering, Galgotias University, Greater Noida, India. 

Manuscript received on May 25, 2020. | Revised Manuscript received on June 29, 2020. | Manuscript published on July 30, 2020. | PP: 1072-1076 | Volume-9 Issue-2, July 2020. | Retrieval Number: B4066079220/2020©BEIESP | DOI: 10.35940/ijrte.B4066.079220
Open Access | Ethics and Policies | Cite | Mendeley
© 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: Biometric Recognition is process which plays a vital role in many fields like security, authenticity, identification. The term biometric is the biological parts of humans which have a unique feature to isolate the individuals. Iris, fingerprint, palm, vascular pattern, voice, signature, face, DNA are the biometrics which are available in the world. Still there are few more biometric exist with unique feature like sclera, the white area of an eye. Blood vessels in sclera area have the unique pattern for every individual. In order to recognize the individuals features if sclera has also used but still how to isolate the feature from the eye image is a question mark. The challenge is the sclera has been surrounded by iris, eyelid and eyelash. Many procedures and methods has been introduced to segment the sclera form the eye but still the efficiency of the approaches has to be evaluated because segmentation accuracy will affect the recognition accuracy. The comparison has been tabulated and the analysis results are briefed in the result. 
Keywords: Digital Image Processing, sclera Recognition, biometrics, feature extraction, Sclera segmentation.