A Segmentation Perspective of Non-Cooperative Iris Recognition
K. Arthi1, M. Rajeev Kumar2
1K. Arthi, Department of CSE, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Avadi, Chennai, Tamil Nadu, India.
2M. Rajeev Kumar, Department of CSE, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Avadi, Chennai, Tamil Nadu, India.
Manuscript received on September 16, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 2405-2411 | Volume-8 Issue-12, October 2019. | Retrieval Number: L29911081219/2019©BEIESP | DOI: 10.35940/ijitee.L2991.1081219
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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: Iris Segmentation, an initial and vital stage of the iris recognition stage which directly affects the recognition accuracy. Especially, the non-cooperative environment that leads to contain many of the noise parameters in the captured image. Since the recognition accuracy of the iris biometrics system is extremely dependent on the proper iris segmentation, this paper is devoted to the segmentation perspective of the non-cooperative iris recognition system. The initial stage of the proposed method is started with applying a hybrid median filter algorithm to remove the possible noises and then a region-based level set algorithm is applied to overcome the identification of the concave property in the non-cooperative iris segmentation and enhanced Otsu’s thresholding method is applied to the pupil segmentation. UBIRIS, a publicly available iris database for the non-cooperative situation, Version 1 and Version 2 is used for the implementation purpose. The accuracy of the segmentation result is achieved as 94.56 and 94.53 for the UBIRISv.1 and UBIRISv.2 respectively which show the proposed method as a better one.
Keywords: Iris Segmentation, Region-based level set Algorithm, Otsu’s Thresholding method, Accuracy.
Scope of the Article: Algorithm Engineering