Histogram of Oriented Gradient Random Template Protection for Face Verification

Abstract

Privacy preserving scheme for face verification is a biometric system embedded with template protection to protect the data in ensuring data integrity. This paper proposes a new method called Histogram of Oriented Gradient Random Template Protection (HOGRTP). The proposed method utilizes Histogram of Oriented Gradient approach as a feature extraction technique and is combined with Random Template Protection method. The proposed method acts as a multi-factor authentication technique and adds a layer of data protection to avoid the compromising biometric issue because biometric is irreplaceable. The performance accuracy of HOGRTP is tested on the unconstrained face images using the benchmarked dataset, Labeled Face in the Wild (LFW). A promising result is obtained to prove that HOGRTP achieves a higher verification rate in percentage than the pure biometric scheme.