Fast palmprint retrieval using speed up robust features

G Kiran Kumar

doi:10.17485/ijst/v13i31.404

Abstract

Background/Objective: Biometric usage is increasing in exponential series in all organisations for multiple purposes like employee attendance, Aadhaar based authentication and secure login using finger print etc. This biometric process should be as quick as possible without making much delay to retrieve the respective finger print. So an efficient quick retrieval procedure is required, in this regards a fast retrieval method for palm prints is proposed in this article. Method: This method uses Speed up Robust Features (SURF) and an efficient look up table for fast retrieval of palm prints. A key is computed for each palmprint by matching with a pre-selected palmprint called representative. This key is used, to place the palmprint into the look up table like traditional database record. To identify a query palmprint, key is computed and selects a set of palm prints from the look up table which are having similar key as possible matches. Findings: This proposed solution is experimented with multiple representative images to check the improved performance. As an outcome we could achieve better hit rate by comparing with existing systemNovelty:. This proposed method makes the new palm prints dynamically without disturbing the current records in the system. The entire solution is experimented on benchmark PolyU palmprint database of 7,753 images and significant performance is shown in results. This proposed solution shows better results with respect to hit rate and miss rate. Keywords: Palmprint; index key; SURF; similarity score; representative

Highlights

Nowadays security is an important issue in every sector including government, business, etc
This paper addresses the above problems and investigates an accurate technique to index palmprints using Speed up Robust Features (SURF) features[16,17,18]
We evaluated the proposed system performance using three measures: Hit Rate (HR), Miss Rate (MR) and Penetration Rate (PR)

Summary

Introduction

Nowadays security is an important issue in every sector including government, business, etc. The use of biometric systems has been increased enormously in every field Many of these biometric frameworks has to manage huge databases and its size is expanding at a quick pace. India’s national ID program known as Unique Identification Authority of India (UIDAI) has a database of more than 700 million individuals. It may reach 1.25 billion individuals in last couple. Recognition of a person in these biometric applications is done by comparing the person‘s biometric sample with all registered samples in the dataset. This linear matching process increases the search time of the system. As a replacement of comparing the query with the whole database, only the samples in the candidate set are compared which increases the query speed and reduces the response time of the system [1]

Methods

Results

Conclusion