An Investigation of Various Segmentation Methods Used in Iris recognition System

Tanni Dhoom; Munmun Biswas

doi:10.5120/ijca2018918009

Iris Segmentation

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i2.5.13956 ◽

2018 ◽

Vol 7 (2.5) ◽

pp. 77

Author(s):

Anis Farihan Mat Raffei ◽

Rohayanti Hassan ◽

Shahreen Kasim ◽

Hishamudin Asmuni ◽

Asraful Syifaa’ Ahmad ◽

...

Keyword(s):

Iris Recognition ◽

Image Data ◽

Recognition System ◽

Environmental Condition ◽

Segmentation Method ◽

Iris Segmentation ◽

Transform Method ◽

Circular Hough Transform ◽

Segmentation Methods

The quality of eye image data become degraded particularly when the image is taken in the non-cooperative acquisition environment such as under visible wavelength illumination. Consequently, this environmental condition may lead to noisy eye images, incorrect localization of limbic and pupillary boundaries and eventually degrade the performance of iris recognition system. Hence, this study has compared several segmentation methods to address the abovementioned issues. The results show that Circular Hough transform method is the best segmentation method with the best overall accuracy, error rate and decidability index that more tolerant to ‘noise’ such as reflection.

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Noncircular Iris Segmentation Based on Weighted Adaptive Hough Transform Using Smartphone Database

Journal of Computational and Theoretical Nanoscience ◽

10.1166/jctn.2018.7154 ◽

2018 ◽

Vol 15 (2) ◽

pp. 739-743 ◽

Cited By ~ 3

Author(s):

Noor Amjed ◽

Fatimah Khalid ◽

Rahmita Wirza O. K. Rahmat ◽

Hizmawati Binit Madzin

Keyword(s):

Hough Transform ◽

Iris Recognition ◽

Recognition System ◽

Iris Segmentation ◽

Negative Image ◽

Processing Step ◽

Segmentation Methods ◽

Segmentation Accuracy ◽

High Level ◽

Imaging Conditions

Iris segmentation methods work based on ideal imaging conditions which produce good output results. However, the segmentation accuracy of an iris recognition system significantly influences its performance, especially with data that captured in unconstrained environment of the Smartphone. This paper proposes a novel segmentation method for unconstrained environment of the Smartphone videos based on choose the best frames from the videos and try to enhance the contrast of this frames by applying the two fuzzy logic membership functions on the negative image which delimit between dark and bright regions in able to make the dark region darker and the bright region brighter. This pre-processing step Facilitates the work of the Weighted Adaptive Hough Transform to automatically find the diameter of the iris region to apply the osiris v4.1. The proposed method results on the video of (Mobile Iris Challenge Evaluation (MICHE))-I, iris databases indicate a high level of accuracy and more efficient computationally using the proposed technique.

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Noisy Iris Segmentation with Reflections Removal Using Probable Boundary Edge Detector

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.236-237.1116 ◽

2012 ◽

Vol 236-237 ◽

pp. 1116-1121 ◽

Cited By ~ 1

Author(s):

Min Wang ◽

Ning Wang ◽

Xiao Gui Yao

Keyword(s):

Iris Recognition ◽

State Of The Art ◽

Image Database ◽

Recognition System ◽

Experimental Results ◽

Boundary Edge ◽

Iris Segmentation ◽

Edge Detector ◽

Segmentation Methods ◽

Segmentation Accuracy

Iris segmentation plays an important role in iris recognition system. Most of segmentation methods are affected by reflection spots, eyelash and eyelid etc. The goal of this work is to accurately segment the iris using Probable boundary (Pb) edge detector after horizontal-vertical weighted reflections removal. Experimental results on the challenging iris image database CASIA-Iris-Thousand with reflection spots sample demonstrate that the iris segmentation accuracy of the proposed methods outperforms state-of-the-art methods.

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Robust Iris Segmentation Algorithm in Non-Cooperative Environments Using Interleaved Residual U-Net

Sensors ◽

10.3390/s21041434 ◽

2021 ◽

Vol 21 (4) ◽

pp. 1434

Author(s):

Yung-Hui Li ◽

Wenny Ramadha Putri ◽

Muhammad Saqlain Aslam ◽

Ching-Chun Chang

Keyword(s):

Iris Recognition ◽

Outer Boundary ◽

Semantic Segmentation ◽

Recognition System ◽

Segmentation Algorithm ◽

Iris Segmentation ◽

Specular Reflections ◽

Boundary Estimation ◽

Segmentation Methods ◽

The Mean

Iris segmentation plays an important and significant role in the iris recognition system. The prerequisite for accurate iris recognition is the correctness of iris segmentation. However, the efficiency and robustness of traditional iris segmentation methods are severely challenged in a non-cooperative environment because of unfavorable factors, for instance, occlusion, blur, low resolution, off-axis, motion, and specular reflections. All of the above factors seriously reduce the accuracy of iris segmentation. In this paper, we present a novel iris segmentation algorithm that localizes the outer and inner boundaries of the iris image. We propose a neural network model called “Interleaved Residual U-Net” (IRUNet) for semantic segmentation and iris mask synthesis. The K-means clustering is applied to select saliency points set in order to recover the outer boundary of the iris, whereas the inner border is recovered by selecting another set of saliency points on the inner side of the mask. Experimental results demonstrate that the proposed iris segmentation algorithm can achieve the mean IOU value of 98.9% and 97.7% for inner and outer boundary estimation, respectively, which outperforms the existing approaches on the challenging CASIA-Iris-Thousand database.

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IRIS AND FINGER VEIN MULTI MODEL RECOGNITION SYSTEM BASED ON SIFT FEATURES

Journal of Advanced Sciences and Engineering Technologies ◽

10.32441/jaset.v1i2.119 ◽

2018 ◽

Vol 1 (2) ◽

pp. 34-44

Author(s):

Faris E Mohammed ◽

Dr. Eman M ALdaidamony ◽

Prof. A. M Raid

Keyword(s):

Iris Recognition ◽

Recognition Performance ◽

Recognition System ◽

Individual Identification ◽

Work Place ◽

Identification Process ◽

Finger Vein ◽

Noise Point ◽

Vein Recognition ◽

A New Technique

Individual identification process is a very significant process that resides a large portion of day by day usages. Identification process is appropriate in work place, private zones, banks …etc. Individuals are rich subject having many characteristics that can be used for recognition purpose such as finger vein, iris, face …etc. Finger vein and iris key-points are considered as one of the most talented biometric authentication techniques for its security and convenience. SIFT is new and talented technique for pattern recognition. However, some shortages exist in many related techniques, such as difficulty of feature loss, feature key extraction, and noise point introduction. In this manuscript a new technique named SIFT-based iris and SIFT-based finger vein identification with normalization and enhancement is proposed for achieving better performance. In evaluation with other SIFT-based iris or SIFT-based finger vein recognition algorithms, the suggested technique can overcome the difficulties of tremendous key-point extraction and exclude the noise points without feature loss. Experimental results demonstrate that the normalization and improvement steps are critical for SIFT-based recognition for iris and finger vein , and the proposed technique can accomplish satisfactory recognition performance. Keywords: SIFT, Iris Recognition, Finger Vein identification and Biometric Systems. © 2018 JASET, International Scholars and Researchers Association

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