scholarly journals Novel Approaches to Improve Iris Recognition System Performance Based on Local Quality Evaluation and Feature Fusion

2014 ◽  
Vol 2014 ◽  
pp. 1-21 ◽  
Author(s):  
Ying Chen ◽  
Yuanning Liu ◽  
Xiaodong Zhu ◽  
Huiling Chen ◽  
Fei He ◽  
...  
Keyword(s):  
Iris Recognition ◽  
Quality Evaluation ◽  
Feature Fusion ◽  
Recognition System ◽  
Experimental Results ◽  
Iris Image ◽  
Local Quality ◽  
Evaluation Algorithm ◽  
Evaluation Parameters

For building a new iris template, this paper proposes a strategy to fuse different portions of iris based on machine learning method to evaluate local quality of iris. There are three novelties compared to previous work. Firstly, the normalized segmented iris is divided into multitracks and then each track is estimated individually to analyze the recognition accuracy rate (RAR). Secondly, six local quality evaluation parameters are adopted to analyze texture information of each track. Besides, particle swarm optimization (PSO) is employed to get the weights of these evaluation parameters and corresponding weighted coefficients of different tracks. Finally, all tracks’ information is fused according to the weights of different tracks. The experimental results based on subsets of three public and one private iris image databases demonstrate three contributions of this paper. (1) Our experimental results prove that partial iris image cannot completely replace the entire iris image for iris recognition system in several ways. (2) The proposed quality evaluation algorithm is a self-adaptive algorithm, and it can automatically optimize the parameters according to iris image samples’ own characteristics. (3) Our feature information fusion strategy can effectively improve the performance of iris recognition system.

scholarly journals A Novel Iris Segmentation Scheme

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Chen-Chung Liu ◽  
Pei-Chung Chung ◽  
Chia-Ming Lyu ◽  
Jui Liu ◽  
Shyr-Shen Yu
Keyword(s):  
Hough Transform ◽  
Iris Recognition ◽  
Image Database ◽  
Recognition System ◽  
Experimental Results ◽  
Circle Fitting ◽  
Iris Segmentation ◽  
Iris Image ◽  
Conventional Methods ◽  
Key Steps

One of the key steps in the iris recognition system is the accurate iris segmentation from its surrounding noises including pupil, sclera, eyelashes, and eyebrows of a captured eye-image. This paper presents a novel iris segmentation scheme which utilizes the orientation matching transform to outline the outer and inner iris boundaries initially. It then employs Delogne-Kåsa circle fitting (instead of the traditional Hough transform) to further eliminate the outlier points to extract a more precise iris area from an eye-image. In the extracted iris region, the proposed scheme further utilizes the differences in the intensity and positional characteristics of the iris, eyelid, and eyelashes to detect and delete these noises. The scheme is then applied on iris image database, UBIRIS.v1. The experimental results show that the presented scheme provides a more effective and efficient iris segmentation than other conventional methods.

Study on Iris Segmentation Method Using Chan-Vese Model

2013 ◽  
Vol 753-755 ◽  
pp. 2995-2999
Author(s):  
Ying Chen ◽  
Feng Yu Yang
Keyword(s):  
Iris Recognition ◽  
Recognition System ◽  
Experimental Results ◽  
Segmentation Method ◽  
Iris Segmentation ◽  
Iris Localization ◽  
Zero Crossing ◽  
Critical Step ◽  
Iris Image ◽  
Pros And Cons

The first and critical step in the process of an iris recognition system is iris segmentation. Firstly, we detailedly describe the process of pupil and iris localization based on Chan-Vese model. Secondly, we describe the process of unwrapping iris annule region, and obtain rectangular image with the same width but different height. Thirdly, cut rectangular iris image to get normalized image. Fourthly, Multi-channel 2D Gabor, 1-D wavelets and zero-crossing methods were used to extract feature; consequently, decidability indexes of intra-class and inter-class were obtained. Finally, comparatively analyze the pros and cons of the proposed method. Three public iris images databases were taken as experimental samples, the experimental results on these image samples demonstrate that the proposed algorithm has certain advantage.

scholarly journals Blind Quality Assessment of Iris Images Acquired in Visible Light for Biometric Recognition

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1308 ◽  
Author(s):  
Mohsen Jenadeleh ◽  
Marius Pedersen ◽  
Dietmar Saupe
Keyword(s):  
Image Quality ◽  
Visible Light ◽  
Iris Recognition ◽  
Recognition Performance ◽  
Rejection Rate ◽  
Recognition System ◽  
Poor Quality ◽  
Iris Image ◽  
Recognition Systems

Image quality is a key issue affecting the performance of biometric systems. Ensuring the quality of iris images acquired in unconstrained imaging conditions in visible light poses many challenges to iris recognition systems. Poor-quality iris images increase the false rejection rate and decrease the performance of the systems by quality filtering. Methods that can accurately predict iris image quality can improve the efficiency of quality-control protocols in iris recognition systems. We propose a fast blind/no-reference metric for predicting iris image quality. The proposed metric is based on statistical features of the sign and the magnitude of local image intensities. The experiments, conducted with a reference iris recognition system and three datasets of iris images acquired in visible light, showed that the quality of iris images strongly affects the recognition performance and is highly correlated with the iris matching scores. Rejecting poor-quality iris images improved the performance of the iris recognition system. In addition, we analyzed the effect of iris image quality on the accuracy of the iris segmentation module in the iris recognition system.

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.  

A ROBUST IRIS LOCALIZATION ALGORITHM VIA RADIAL SYMMETRY FOR NONIDEAL CAPTURING CONDITION

2009 ◽  
Vol 23 (01) ◽  
pp. 45-57 ◽  
Author(s):  
WEN-CONG ZHANG ◽  
BIN LI ◽  
XUE-YI YE ◽  
ZHEN-QUAN ZHUANG ◽  
KONG-QIAO WANG
Keyword(s):  
Iris Recognition ◽  
Recognition System ◽  
Radial Symmetry ◽  
Precise Localization ◽  
Localization Algorithm ◽  
Time System ◽  
Iris Localization ◽  
Real Time System ◽  
The Ideal

Iris localization is a key component of practical iris recognition system. Previous algorithms show good localization performances for iris images captured in the ideal conditions. However, in practice, the quality of iris image is greatly influenced by luminance, eyelashes, hair or glasses frame, which will cause mislocalization. In order to improve the robustness of iris localization, this paper proposes a new localization algorithm based on the radial symmetry transform, in which the radial symmetry characteristic of the pupil is utilized to realize iris localization. Experimental results show that the proposed algorithm can efficiently avoid the interference of luminance and other bad conditions, and realize robust precise localization in a real-time system.

scholarly journals Soft Lens Detection in Iris Image using Lens Boundary Analysis and Pattern Recognition Approach

2021 ◽  
Vol 10 (1) ◽  
pp. 241-250
Keyword(s):  
Pattern Recognition ◽  
Iris Recognition ◽  
Recognition System ◽  
Detection Algorithm ◽  
Iris Image ◽  
Ridge Detection ◽  
Visibility Condition ◽  
Pattern Recognition Approach ◽  
Contact Lens Detection ◽  
False Reject Rate

Recent studies have demonstrated that the soft lens wearing during iris recognition has indicated the increase of false reject rate. It denies the strong belief that the soft lens wearing will cause no performance degradation. Therefore, it is a necessity for an iris recognition system to be able to detect the presence of soft lens prior to iris recognition. As a first step towards soft lens detection, this study proposed a method for segmenting the soft lens boundary in iris images. However, segmenting the soft lens boundary is a very challenging task due to its marginal contrast. Besides, the flash lighting effect during the iris image enrolment has caused the image to suffer from inconsistent illumination. In addition, the visibility condition of the soft lens boundary may be discerned as a bright or dark ridge as a result of the flash lighting. Three image enhancement techniques were therefore proposed in order to enhance the contrast of the soft lens boundary and to provide an even distribution of intensities across the image. A method called summed-histogram has been incorporated as a solution to classify the visibility condition of the soft lens boundary automatically. The visibility condition of the ridge is used to determine the directional directive magnitude by the ridge detection algorithm. The proposed method was evaluated with Notre Dame Contact Lens Detection 2013 database. Results showed that the proposed method has successfully segment the soft lens boundary with an accuracy of over 92%.

Boundary Detection for Non-Ideal Iris Based on Gray Transform

2013 ◽  
Vol 441 ◽  
pp. 682-686
Author(s):  
Hong Lin Wan ◽  
Bao Sheng Li ◽  
Hong Sheng Li
Keyword(s):  
Iris Recognition ◽  
Outer Boundary ◽  
Boundary Detection ◽  
Recognition System ◽  
Experimental Results ◽  
Low Contrast ◽  
Localization Accuracy ◽  
Localization Method ◽  
Key Issues

Boundary localization is one of the key issues for reliable iris recognition system. For non-ideal iris images, eyelashes or eyelids occlusions and low contrast between iris and sclera will lead to inaccurate boundary localization. Specifically, if the intensive transition from iris to sclera is too smooth, outer boundary localization will be very difficult. To stress the problem, in this paper the boundary localization method is proposed in which nonlinear gray transformation is innovated in outer boundary localization process. The experimental results depict that our algorithm have improved the localization accuracy for non-ideal iris compared to the classical algorithms.

scholarly journals Iris Recognition at-a-Distance by Means of Chronological MBO-Based DBN

2019 ◽  
Vol 8 (12) ◽  
pp. 4540-4552
Keyword(s):  
Hough Transform ◽  
Iris Recognition ◽  
Monarch Butterfly ◽  
Recognition System ◽  
Monarch Butterfly Optimization ◽  
Iris Image ◽  
Safety Reason ◽  
Local Gradient ◽  
Detection Schemes ◽  
Actual Method

Now a days, Iris recognition is wieldy used for the identification of person. The superior bit of 1 countries exploits biometric system for safety reason with the conclusion goal that in runway boarding, custom freedom, gathering passage, etc. The Iris detection at-a-Distance (IAAD) framework is generally used to identify the person in most of the applications. In this system, different features of iris image are extracted in addition enhances the superiority of iris image. Over the span of the most recent ages there consume raised various structures to design and finish iris affirmation systems which works at longer separation going from one meter to sixty meter. Because of such long scope of iris detection schemes in addition iris attainment scheme provides for the best applications to the client. Therefore, It is necessary to design an effective algorithm for IAAD is necessary. In this article, an actual method for iris recognition is presents. A Chronological Monarch Butterfly Optimization -based Deep Belief Network (Chronological MBO-based DBN) technique is anticipated for iris detection.This technique algorithm is the combination of Chronological theory with the Monarch Butterfly Optimization. It is utilized to mastermind the sequential presumption of an iris picture. Additionally, the Hough Transform calculation is utilized for discovery of iris circle and edge. To enhance the accuracy of anticipated iris recognition system ScatT-Loop descriptor and the Local Gradient Pattern (LGP) are fed to the Chronological MBO-based DBN algorithm and these are castoff to abstract the dissimilar features of an iris picture. The dataset used for these tactices are UBIRIS.v1 For the normalization and segmentation of an iris image is done by by means of Dougman's rubber sheet model. This system is established on MATLAB for executing the Hough transform procedures also for reading the iris images. The simulation results shows that this system successfully recognize the iris at a distance 4 to 8 meter. Different performance parameters like as FAR accuracy, too FRR shows better results in this anticipated work.

Noisy Iris Segmentation with Reflections Removal Using Probable Boundary Edge Detector

2012 ◽  
Vol 236-237 ◽  
pp. 1116-1121 ◽  
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.

scholarly journals An improved iris recognition system based on the fusion of the curvelet and DTCWT

2020 ◽  
pp. 8-12
Author(s):  
Nguyen Nam Phuc, Le Tien Hung, Nguyen Quoc Trung, Ha Huu Huy Nguyen
Keyword(s):  
Wavelet Transform ◽  
Random Forest ◽  
Iris Recognition ◽  
Recognition System ◽  
High Accuracy ◽  
Random Forest Classifier ◽  
Experimental Results ◽  
Complex Wavelet Transform ◽  
Decision Level ◽  
Complex Wavelet

In recent years, iris recognition has been emerged as one of the most popular biometric techniques because it guarantees high universality, distinctiveness, permanence, collectability, performance, acceptability, circumvention. In the paper we propose an improved system for iris recognition with high accuracy by fusing curvelet and dual tree complex wavelet transform. In our system, the main features are extracted from pre-processed/normalized iris images using both curvelet and Dual Tree Complex Wavelet Transform (DTCWT) tranforms. After performing different classifiers independently, all the results are fused to get final classification in the decision level to increase the accuracy of system. Finally, the random forest classifier and CATIA dataset are used to measure the performance of the proposed method. The experimental results show that the technique of the paper based on fusion of the curvelet and DTCWT is promising when compared with other existing similar techniques.

Sign in / Sign up

Export Citation Format

Share Document