Iris Segmentation for Non-ideal Images

2015 ◽  
Vol 74 (3) ◽  
Author(s):  
Nasharuddin Zainal ◽  
Abduljalil Radman ◽  
Mahamod Ismail ◽  
Md Jan Nordin
Keyword(s):  
Iris Recognition ◽  
Recognition Algorithm ◽  
Segmentation Method ◽  
Iris Segmentation ◽  
West Virginia University ◽  
Segmentation Methods ◽  
Biometric Systems ◽  
Segmentation Algorithms ◽  
Recognition Systems ◽  
Constrained Conditions

Iris recognition has been regarded as one of the most reliable biometric systems over the past years. Previous studies have shown that the performance of iris recognition systems highly dependent on the performance of their segmentation algorithms. Iris segmentation is the process to isolate the iris region from the surrounded structures of the eye image. However, several iris segmentation algorithms have been developed in the literature, but their segmentation and recognition accuracies drastically degrade with non-ideal iris images acquired in less constrained conditions. Thus, it is crucial to develop a new iris segmentation method to improve iris recognition using non-ideal images. Hence, the objective of this paper is an iris segmentation method on the basis of optimization to isolate the iris region from non-ideal iris images such those affected by reflections, blurred boundaries, eyelids occlusion, and gaze-deviation. Experimental results on the off axis/angle West Virginia University (WVU) iris database demonstrated the superiority of the developed method over state-of-the-art iris segmentation methods considered in this paper. The performance of an iris recognition algorithm based on the developed iris segmentation method was observed to be improved.  

scholarly journals Iris Segmentation

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.  

Age dependency of the diabetes effects on the iris recognition systems performance evaluation results

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Mohammadreza Azimi ◽  
Seyed Ahmad Rasoulinejad ◽  
Andrzej Pacut
Keyword(s):  
Iris Recognition ◽  
Recognition Task ◽  
Aging Effect ◽  
Recognition System ◽  
Health Condition ◽  
Age Dependency ◽  
Biometric Systems ◽  
Kolmogorov Smirnov ◽  
Recognition Systems ◽  
Smirnov Test

AbstractIn this paper, we attempt to answer the questions whether iris recognition task under the influence of diabetes would be more difficult and whether the effects of diabetes and individuals’ age are uncorrelated. We hypothesized that the health condition of volunteers plays an important role in the performance of the iris recognition system. To confirm the obtained results, we reported the distribution of usable area in each subgroup to have a more comprehensive analysis of diabetes effects. There is no conducted study to investigate for which age group (young or old) the diabetes effect is more acute on the biometric results. For this purpose, we created a new database containing 1,906 samples from 509 eyes. We applied the weighted adaptive Hough ellipsopolar transform technique and contrast-adjusted Hough transform for segmentation of iris texture, along with three different encoding algorithms. To test the hypothesis related to physiological aging effect, Welches’s t-test and Kolmogorov–Smirnov test have been used to study the age-dependency of diabetes mellitus influence on the reliability of our chosen iris recognition system. Our results give some general hints related to age effect on performance of biometric systems for people with diabetes.

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

2018 ◽  
Vol 15 (2) ◽  
pp. 739-743 ◽  
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.

Detecting Eyelash and Reflection for Accurate Iris Segmentation

2003 ◽  
Vol 17 (06) ◽  
pp. 1025-1034 ◽  
Author(s):  
Wai-Kin Kong ◽  
David Zhang
Keyword(s):  
Statistical Model ◽  
Iris Recognition ◽  
Segmentation Method ◽  
Iris Segmentation ◽  
Edge Detector ◽  
Recognition Error ◽  
Weak Reflection

Accurate iris segmentation is presented in this paper, which is composed of two parts, reflection detection and eyelash detection. Eyelashes are classified into two categories, separable and multiple. An edge detector is applied to detect separable eyelashes, and intensity variances are used to recognize multiple eyelashes. Reflection is also divided into two types, strong and weak. A threshold and statistical model is proposed to recognize the strong and weak reflection, respectively. We have developed an iris recognition approach for testing the effectiveness of the proposed segmentation method. The results show that the proposed method can reduce recognition error for the iris recognition approach.

Research on Threshold Segmentation Algorithms

2013 ◽  
Vol 860-863 ◽  
pp. 2888-2891
Author(s):  
Yu Bing Dong ◽  
Ming Jing Li ◽  
Ying Sun
Keyword(s):  
Pattern Recognition ◽  
Image Segmentation ◽  
Segmentation Method ◽  
Threshold Segmentation ◽  
Segmentation Methods ◽  
Segmentation Algorithms ◽  
Better Than ◽  
Iterative Threshold

Thresholding is one of the critical steps in pattern recognition and has a significant effect on the upcoming steps of image application, the important objectives of thresholding are as follows, and separating objects from background, decreasing the capacity of data consequently increases speed. Various threshold segmentation methods are studied. These methods are compared by using MATLAB7.0. The qualities of image segmentation are elaborated. The results show that iterative threshold segmentation method is better than others.

scholarly journals RELIABILITY INDEX FOR IRIS CODE MATCHING IN IRIS RECOGNITION SYSTEMS

2019 ◽  
Vol XLII-2/W12 ◽  
pp. 197-202
Author(s):  
B. H. Shekar ◽  
S. S. Bhat ◽  
A. Maysuradze
Keyword(s):  
System Reliability ◽  
Reliability Index ◽  
Iris Recognition ◽  
Recognition Accuracy ◽  
Simulation Experiments ◽  
Factors Affecting ◽  
Biometric Systems ◽  
Recognition Systems ◽  
Matching Techniques ◽  
Rejection Rates

<p><strong>Abstract.</strong> Iris code matching is an important stage of iris biometric systems which compares the input iris code with stored patterns of enrolled iris codes and classifies the code into one of classes so that, the claim is accepted or rejected. Several classifier based approaches are proposed by the researchers to improve the recognition accuracy. In this paper, we discuss the factors affecting an iris classifier’s performance and we propose a reliability index for iris matching techniques to quantitatively measure the extent of system reliability, based on false acceptance rate and false rejection rates using Monte Carlo Simulation. Experiments are carried out on benchmark databases such as, IITD, MMU v-2, CASIA v-4 Distance and UBIRIS v.2.</p>

The Design of Library Management System Based on Internet of Things and Hand Lines Recognition System

2014 ◽  
Vol 672-674 ◽  
pp. 1985-1990 ◽  
Author(s):  
Wang Fang
Keyword(s):  
Management System ◽  
Iris Recognition ◽  
Recognition Performance ◽  
Recognition System ◽  
Recognition Algorithm ◽  
Fingerprint Recognition ◽  
Library Management ◽  
Material Resources ◽  
Library Management System ◽  
Biometric Systems

For an ordinary individual biometric systems and technology, such as fingerprint recognition, palm recognition, face recognition or iris recognition, or late detection from a single object has crippled so that they have the characteristics of unity and limitations, this paper combining fingerprint and hand palm pattern recognition technology, taking into account the complexity of the image pattern and diversity, we propose a dual recognition algorithm, which greatly makes up for lack of a single fingerprint or palm print recognition method. The technology used in library management system than traditional card-borrowed books have higher efficiency and save manpower and material resources. After the experimental statistics, and achieved the desired results, not only improve the recognition efficiency, but also to ensure the accuracy of the recognition performance.

Research on CCD Infrared Image Threshold Segmentation

2012 ◽  
Vol 220-223 ◽  
pp. 1292-1297
Author(s):  
Xing Ma ◽  
Jun Li Han ◽  
Chang Shun Liu
Keyword(s):  
Image Segmentation ◽  
Automatic Segmentation ◽  
Infrared Image ◽  
Experimental System ◽  
Segmentation Method ◽  
Gray Scale ◽  
Image Detection ◽  
Segmentation Methods ◽  
Segmentation Algorithms ◽  
Characteristics Analysis

In recent years, the gray-scale thresholding segmentation has emerged as a primary tool for image segmentation. However, the application of segmentation algorithms to an image is often disappointing. Based on the characteristics analysis of infrared image, this paper develops several gray-scale thresholding segmentation methods capable of automatic segmentation in regions of pedestrians of infrared image. The approaches of gray-scale thresholding segmentation method are described. Then the experimental system is established by using the infrared CCD device for pedestrian image detection. The image segmentation results generated by the algorithm in the experiment demonstrate that the Otsu thresholding segmentation method has achieved a kind of algorithm on automatic detection and segmentation of infrared image information in regions of interest of image.

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