Fusion of Dual-Tree Complex Wavelets and Local Binary Patterns for Iris Recognition

2014 ◽  
pp. 167-177
Author(s):  
N. L. Manasa ◽  
A. Govardhan ◽  
Ch. Satyanarayana
Keyword(s):  
Iris Recognition ◽  
Local Binary Patterns ◽  
Complex Wavelets

scholarly journals Iris Identification Based on the Fusion of Multiple Methods

2021 ◽  
pp. 1364-1375
Author(s):  
Asaad Noori Hashim ◽  
Roaa Razaq Al-Khalidy
Keyword(s):  
Iris Recognition ◽  
Local Binary Patterns ◽  
Histogram Equalization ◽  
Recognition System ◽  
Scale Invariant ◽  
Invariant Feature ◽  
Scale Invariant Feature ◽  
City Block Distance ◽  
Iris Identification ◽  
The City

Iris recognition occupies an important rank among the biometric types of approaches as a result of its accuracy and efficiency. The aim of this paper is to suggest a developed system for iris identification based on the fusion of scale invariant feature transforms (SIFT) along with local binary patterns of features extraction. Several steps have been applied. Firstly, any image type was converted to  grayscale. Secondly, localization of the iris was achieved using circular Hough transform. Thirdly, the normalization to convert the polar value to Cartesian using Daugman’s rubber sheet models, followed by histogram equalization to enhance the iris region. Finally, the features were extracted by utilizing the scale invariant feature transformation and local binary pattern. Some sigma and threshold values were used for feature extraction, which achieved the highest rate of recognition. The programming was implemented by using MATLAB 2013. The matching was performed by applying the city block distance. The iris recognition system was built with the use of iris images for 30 individuals in the CASIA v4. 0 database. Every individual has 20 captures for left and right, with a total of 600 pictures. The main findings showed that the values of recognition rates in the proposed system are 98.67% for left eyes and 96.66% for right eyes, among thirty subjects.

IRIS RECOGNITION METHOD BASED ON GABOR FILTERS AND UNIFORM LOCAL BINARY PATTERNS

2012 ◽  
Vol 12 (02) ◽  
pp. 1250014 ◽  
Author(s):  
NADIA FEDDAOUI ◽  
HELA MAHERSIA ◽  
KAMEL HAMROUNI
Keyword(s):  
Iris Recognition ◽  
Hamming Distance ◽  
Local Binary Patterns ◽  
Gabor Filters ◽  
Global Information ◽  
Gabor Filtering ◽  
Recognition Method ◽  
Global Features ◽  
Statistical Measures ◽  
Local Arrangement

Iris recognition has been recently given greater attention in human identification and it is becoming increasingly an active topic in research. This paper presents a novel iris recognition method based on multi-channel Gabor filtering and uniform local binary patterns (ULBP). First, the eye image is processed in order to obtain a segmented and normalized eye image by applying Hough transform and polar transformation. Second, the iris image is analyzed by Gabor filters to extract the global features of texture details. Then, ULBP operators are applied in each transformed image to describe the local arrangement of iris texture patterns. Next, the obtained representation is partitioned in blocks. Finally, we have encoded the local relationships between statistical measures computed in blocks to form a template of 240 bytes. We estimate the similarity between irises by computing the modified Hamming distance between templates. Tests were carried out on CASIA v3 iris database. Experimental results illustrate the effectiveness and robustness of ULBP to extract rich local and global information of iris texture when combined with simultaneously multi-blocks and multi-channel method. The comparative evaluations illustrate the good discriminative properties of extracted features for iris recognition.

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    

Survey on Segmentation to Iris Recognition System

2012 ◽  
Vol 3 (4) ◽  
pp. 514-515
Author(s):  
Meenakshi BK Meenakshi BK ◽  
◽  
Prasad M R Prasad M R
Keyword(s):  
Iris Recognition ◽  
Recognition System

A Survey on Iris Recognition System

2019 ◽  
Vol 7 (7) ◽  
pp. 302-307
Author(s):  
Prabhat Kumar ◽  
Manish Ahirwar ◽  
Anjna Deen
Keyword(s):  
Iris Recognition ◽  
Recognition System
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