Two Approaches Based on Genetic Algorithm to Generate Short Iris Codes

Abstract

This paper has the following contributions in iris recognition compass: first, novel parameters selection for Gabor filters to extract the iris features. Second, due to iris textures randomness and assigning the Gabor parameters by pre-knowledgeable values, traditionally, a large Gabor filter bank has been used to prevent losing the discriminative informat ion. It leads to perform extracting and matching the features heavily and on the other hand, the generated feature vectors are lengthened as required for extra storage space. We have proposed and compared two different approaches based on Genetic Algorithm to reduce the system co mplexity: optimizing the Gabor parameters and feature selection. Third, proposing a novel encoding strategy based on the texture variat ions to generate compact iris codes. The experimental results show that generated iris codes by optimizing the Gabor parameters approach is mo re distinctive and compact than ones based on feature selection approach. Since 2003 he has been on the faculty of the Depart ment of Teleco mmunication Eng ineering, Shiraz University of Technology, Shiraz, Iran. His activities have included Image signal processing, digital filter structures, filter banks, wavelet based signal processing and wireless communication. He is a Member of the IEEE.Habi bol ah Danyali received the B.Sc. and M.Sc. degrees in Electrical Engineering respectively fro m the

Shape adaptive, robust iris feature extraction from noisy iris images

“…The Gabor filter bank which is used here has four filters that the Gabor parameters selection is done by reported values in our earlier work. [6] The size of the image blocks and Gabor filters is 9 × 9 (i.e., n = 9) as P = 8 and Q = 64. Therefore, the iris codes and mask codes contain 2048 bits.…”

“…In order to avoid the noise-removing step, some authors[456] proposed using of some portions of the iris where are less occluded by artifacts. Although this strategy reduces processing time, the recognition accuracy is reduced especially for large scale due to using partial discriminant information.…”

“…In our earlier work[6] a novel Gabor parameter selection has been proposed and the Gabor parameters values have been optimized using multi objective genetic algorithm. The right upper quarter of normalized iris image was used for feature extraction in order to omit the noise-removing step in our earlier work.…”

“…However, in this paper, our optimized Gabor-wavelet is used to extract the features from whole normalized image using the reported values in. [6] The iris codes are obtained by extending the novel iris encoding strategy, namely Amplitude Texture Variations which was proposed in,[6] to whole normalized iris image as follows.…”

Biometric System Design for Iris Recognition Using Intelligent Algorithms

“…In 2012, Ghodrati et al proposed a novel approaches for extracting the iris features sing Gabor filters. The Genetic algorithm was proposed to compare two different templates [6]. Gabor approach was more distinctive and compact on feature selection approach.…”