scholarly journals Efficient Unconstrained Iris Recognition System Based on CCT-Like Mask Filter Bank

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Hala N. Fathee ◽  
Osman N. Ucan ◽  
Jassim M. Abdul-Jabbar ◽  
Oguz Bayat
Keyword(s):  
Filter Bank ◽  
Iris Recognition ◽  
Feature Vector ◽  
Recognition System ◽  
Personal Identification ◽  
Computation Complexity ◽  
System Realization ◽  
Lower Complexity ◽  
Image Transform ◽  
Improved Performance

In this paper, a new personal identification method based on unconstrained iris recognition is presented. We apply a nontraditional step for feature extraction where a new circular contourlet filter bank is used to capture the iris characteristics. This idea is based on a new geometrical image transform called the circular contourlet transform (CCT). An efficient multilevel and multidirectional contourlet decomposition method is needed to form a reduced-length quantized feature vector with improved performance. The CCT transform provides both multiscale and multioriented analysis of iris features. Circular contourlet-like mask filters can be used with shapes just like the 2D circular-support regions in different scales and directions. A reduced recognition system is realized using a single branch of the whole decomposition bank, highlighting a system realization with lower complexity and fewer computations. In the proposed recognition system, only five out of seven elements of the gray level cooccurrence matrix are required in the creation of the feature vector, which leads to a further reduction in computations. In addition, the highly discriminative frequency regions due to the use of circular-support decompositions can result in highly accurate feature vectors, reflecting good recognition rates for the proposed system. It is shown that the proposed system has encouraging performance in terms of high recognition rates and a reduced number of elements of the feature vector. This reflects reliable and rapid recognition properties. In addition, some promising characteristics of the system are apparent since it can efficiently be realized with lower computation complexity.

scholarly journals A Review of Iris Recognition Algorithms

2017 ◽  
Vol 1 (4-2) ◽  
pp. 175
Author(s):  
Abdulrahman Aminu Ghali ◽  
Sapiee Jamel ◽  
Kamaruddin Malik Mohamad ◽  
Nasir Abubakar Yakub ◽  
Mustafa Mat Deris
Keyword(s):  
Iris Recognition ◽  
Hamming Distance ◽  
Gabor Filter ◽  
Recognition System ◽  
Personal Identification ◽  
Border Control ◽  
Biometric System ◽  
Rubber Sheet ◽  
Automated Teller Machines ◽  
Recognition Algorithms

With the prominent needs for security and reliable mode of identification in biometric system. Iris recognition has become reliable method for personal identification nowadays. The system has been used for years in many commercial and government applications that allow access control in places such as office, laboratory, armoury, automated teller machines (ATMs), and border control in airport. The aim of the paper is to review iris recognition algorithms. Iris recognition system consists of four main stages which are segmentation, normalization, feature extraction and matching. Based on the findings, the Hough transform, rubber sheet model, wavelet, Gabor filter, and hamming distance are the most common used algorithms in iris recognition stages.  This shows that, the algorithms have the potential and capability to enhanced iris recognition system. 

Adoption of Dual Iris and Periocular Recognition for Human Identification

2016 ◽  
pp. 250-266
Author(s):  
R. Deepika ◽  
M. R. Prasad ◽  
Srinivas Chetana ◽  
T. C. Manjunath
Keyword(s):  
Iris Recognition ◽  
Recognition System ◽  
Personal Identification ◽  
Iris Segmentation ◽  
Biometric System ◽  
Multiple Features ◽  
Facial Region ◽  
Multimodal Biometric System ◽  
Segmentation Approach ◽  
Periocular Recognition

Personal identification from the iris images acquired under less-constrained imaging environment is highly challenging. Such environment requires the development of efficient iris segmentation approach and recognition strategy which can exploit multiple features available for the potential identification. So, along with the iris features periocular features have increasing attention in biometrics technology. For the recognition purpose iris and periocular information are collected from both the eyes of same person simultaneously. The term periocular refers to the facial region in the immediate vicinity of the eye. Acquisition of image for periocular biometric is expected to require less subject cooperation. In this chapter, a dual iris based multimodal biometric system that increases the performance and accuracy of the typical iris recognition system is proposed.

scholarly journals A NEURAL NETWORK BASED IRIS RECOGNITION SYSTEM FOR PERSONAL IDENTIFICATION

2010 ◽  
Vol 1 (2) ◽  
pp. 78-84 ◽  
Author(s):  
Usham Dias ◽  
◽  
Vinita Frietas ◽  
Sandeep P S ◽  
Amanda Fernandes ◽  
...  
Keyword(s):  
Neural Network ◽  
Iris Recognition ◽  
Recognition System ◽  
Personal Identification

scholarly journals Assessment on Extraction and Matching of Finger Vein and Iris Pattern based Authentication System

2020 ◽  
Vol 8 (5) ◽  
pp. 4182-4194
Keyword(s):  
Iris Recognition ◽  
Recognition System ◽  
Personal Identification ◽  
The Body ◽  
Infrared Light ◽  
Vein Pattern ◽  
Finger Vein ◽  
Line Tracking ◽  
Authentication System ◽  
Future Work

Biometrics uses human behavioral features for personal identification and has become most popular and promising alternatives than the traditional methods. The vein pattern is hidden inside the body and hence the problem of forgery in vein is consequently reduced when compared to fingerprint. Iris is one of the most reliable biometric traits due to its uniqueness and stability. The uniqueness of iris texture comes from the random and complex structures such as furrows, ridges, crypts, rings, corona, and freckles etc. which are formed during gestation. Often iris is combined with other biometric features for robust biometric systems. The finger vein pattern acquired under infrared light is used to design an accurate personal authentication system. The personal identification method based on vein extract the patterns from an unclear original image and line tracking operations with randomly varied start points are repeatedly carried out. This paper reviews various techniques introduced in finger vein and iris recognition system. This paper mainly focuses in introduction about finger vein and iris pattern, survey of existing research works done in the process under finger vein combined with iris recognition such as image acquisition, vein and iris enhancement, vein and iris pattern extraction and vein and iris pattern matching. Finally the challenges and future work are discussed in order to improve the left finger vein pattern with right iris and right finger vein pattern with left iris recognition.

BIOMETRIC PERSONAL IDENTIFICATION ON 2D WAVELET TRANSFORM AND CHI-SQUARED MODEL

2015 ◽  
Vol 14 (9) ◽  
pp. 6074-6084
Author(s):  
Taiwo TundeAdeniyi ◽  
Olatubosun Olabode ◽  
Gabriel B. Iwasokun ◽  
Samuel A. Oluwadare ◽  
Raphael O. Akinyede
Keyword(s):  
Wavelet Transform ◽  
Iris Recognition ◽  
Recognition System ◽  
Personal Identification ◽  
Iris Segmentation ◽  
Rubber Sheet ◽  
Biometric Template ◽  
Chi Squared ◽  
Phase Data

Iris recognition system consists of image acquisition, iris preprocessing, iris segmentation and feature extraction with comparism (matching) stages. The biometric based personal identification using iris requires accurate iris segmentation for successful identification or recognition. Recently, several researchers have implemented various methods for segmentation of boundaries which will require a modification of some of the existing segmentation algorithms for their proper recognition. Therefore, this research presents a 2D Wavelet Transform and Chi-squared model for iris features extraction and recognition. Circular Hough Transform was used for the segmentation of the iris image. The system localizes the circular iris and pupil region and removes the occluding eyelids and eyelashes. The extracted iris region is normalized using Daugman’s rubber sheet model into a rectangular block with constant dimensions to account for imaging inconsistencies. Finally, the phase data (iris signature) from the 2D wavelet transform data is extracted, forming the biometric template. The chi-squared distance is employed for classification of iris templates and recognition. Implementing this model can enhance identification. Based on the designed system, an FAR (False Acceptances ratio) of 0.00 and an FRR (False Rejection Ratio) of 0.896 was achieved.

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

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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