Research on palmprint identification method based on quantum algorithms.

Hui Li,Zhanzhan Zhang

doi:10.1155/2014/670328

Abstract

Quantum image recognition is a technology by using quantum algorithm to process the image information. It can obtain better effect than classical algorithm. In this paper, four different quantum algorithms are used in the three stages of palmprint recognition. First, quantum adaptive median filtering algorithm is presented in palmprint filtering processing. Quantum filtering algorithm can get a better filtering result than classical algorithm through the comparison. Next, quantum Fourier transform (QFT) is used to extract pattern features by only one operation due to quantum parallelism. The proposed algorithm exhibits an exponential speed-up compared with discrete Fourier transform in the feature extraction. Finally, quantum set operations and Grover algorithm are used in palmprint matching. According to the experimental results, quantum algorithm only needs to apply square of N operations to find out the target palmprint, but the traditional method needs N times of calculation. At the same time, the matching accuracy of quantum algorithm is almost 100%.

Highlights

Biological recognition technology is more and more important in this modern society [1]
Palmprint is filtered by using quantum adaptive median filtering algorithm
Compared with the traditional methods, we can see from the filtering effect chart that this method possesses an enhanced ability of filtering and in the meantime conserves palmprint details

Summary

Introduction

Biological recognition technology is more and more important in this modern society [1]. Quantum algorithms are used in the recognition steps including filtering processing, feature extraction, and palmprint matching. 2. Palmprint Filtering Processing Based on Quantum Adaptive Median Filtering Algorithm. In this paper we propose a quantum adaptive median filtering algorithm on palmprint pretreatment. Based on quantum measurements and collapse tenet, median filtering algorithm is applied on the framework of the quantum signal processing. It is an adaptive median filter because it can adaptively adjust the neighbor size and shape; it is based on the local features of translational position of operation template. We apply the binarization processing and pixel flip operation to filtered palmprint in order to benefit from the feature extraction

Palmprint Feature Extraction Based on Quantum Fourier Transform

Findings

Conclusions