Non-Cooperative Iris Segmentation: A Survey
M. Rajeev Kumar1, K. Arthi2
1M. Rajeev Kumar, Department of CSE, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, (Tamil Nadu), India.
2K. Arthi, Department of CSE, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, (Tamil Nadu), India.
Manuscript received on 23 March 2019 | Revised Manuscript received on 30 March 2019 | Manuscript published on 30 March 2019 | PP: 1375-1382 | Volume-7 Issue-6, March 2019 | Retrieval Number: F3010037619/19©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: With the advancement in information technology, human identification based on iris pattern has registered rapid strides in the recent times. Present day research has been focusing on finding a solution to provide secure and reliable identification and verification in human related problems. There has been a paradigm shift in the study of human identification from cooperation to non-cooperation on the part of the subjects. The purpose of this paper is to present a survey to facilitate the researchers, who are in the beginning stage of their investigation in iris recognition, to understand the current trends and the implemented methodologies of the non-cooperative iris segmentation. As the non-cooperation deals with the various heterogeneous factors such as obstruction, occlusions by eyelids and eyelashes and affected with so many noise factors, the segmentation of the iris from the eye image is becoming the ultimate challenge. Most of the authors have concentrated on the identification of eyelids and eyelashes which are quite normal under the non-cooperative situation. In this paper, the following categories of iris segmentation and their implementation are analyzed with: (1) Both the pupil and iris as (i) circular model and their improvements (ii) noncircular model and (2) active contour models.
Keywords: Biometrics, Iris, Segmentation, Computer Vision, Non-cooperation, Pattern Recognition.
Scope of the Article: Human Computer Interactions