Palmprint Recognition Using Hessian Matrix and Two-Component Partition Method

Palmprint Recognition Using Hessian Matrix and Two-Component Partition Method

Jyotismita Chaki (VIT University, Vellore, India) and Nilanjan Dey (JIS University, Kolkata, India)
Copyright: © 2021 |Pages: 22
DOI: 10.4018/IJDCF.2021010102
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Abstract

Palmprint recognition has been comprehensively examined in the past couple of years and various undertakings are done to use it as a biometric methodology for various applications. The point of this study is to construct an effective palmprint recognition technique with low computational multifaceted nature and along these lines to expand the acknowledgment and precision. Since edges are free from distortion, they are very reliable and subsequently used for palm print recognition. The originality of the proposed technique depends on new area of interest (ROI) extraction took after by new principal line extraction and texture matching strategy. The new principal line extraction technique is created by using the Hessian matrix and Eigen value. The texture matching of the ROI is done using new 2-component partition method by segmenting the image into comparative and non-comparative edges. Examinations are finished on a database and exploratory results exhibit that the accuracy of the proposed method is comparable to past methods used for palmprint recognition.
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Introduction

Checking an individual character with high accuracy is desired in various applications, for instance, some national foundations get the opportunity to control, e-keeping cash, exit and passage and so on. Biometric recognizing verification advancement is a kind of strategies to feasibly approve the identity of a man in perspective of physiological or behavioral characteristics. In connection with ID card or secret scratch card, biometric recognizing verification development is very useful, fruitful and secure with many far-reaching applications.

The aim of this study is to construct an effective palmprint recognition technique from the principal lines. Since palm lines are free from distortion, they are very reliable and thus can be used for palmprint recognition. The originality of the proposed technique includes the development of a new method for extracting the region of interest (ROI) followed by new principal line extraction and texture matching technique. The new principal line extraction technique is created by using the Hessian matrix and Eigenvalue. The feature extraction of the ROI is done by using a new 2-component partition method where the principal lines are segmented into comparative and non-comparative edges. The recognition of palmprint image is done by comparing or matching the comparative and non-comparative edges between the training and testing images.

The arrangement of the paper is according to the following: segment 2 describes previous works, segment 3 diagrams the proposed approach, segment 4 gives the details of experimentation and results, segment 5 analyzes the proposed approach with other contemporary methodologies, while segment 6 mentions the general conclusions.

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