Identification via Retinal Vessels Combining LBP and HOG

TL;DR

This paper introduces a new retinal identification method combining LBP and HOG techniques, aiming for accurate vessel separation and improved recognition performance under rotation and size variations.

Contribution

The paper presents a novel retinal identification approach using combined LBP and HOG features, enhancing vessel separation and recognition accuracy.

Findings

Better performance compared to recent methods

Effective vessel separation using machine vision techniques

Robustness to rotation and size changes

Abstract

With development of information technology and necessity for high security, using different identification methods has become very important. Each biometric feature has its own advantages and disadvantages and choosing each of them depends on our usage. Retinal scanning is a bio scale method for identification. The retina is composed of vessels and optical disk. The vessels distribution pattern is one the remarkable retinal identification methods. In this paper, a new approach is presented for identification via retinal images using LBP and hog methods. In the proposed method, it will be tried to separate the retinal vessels accurately via machine vision techniques which will have good sustainability in rotation and size change. HOG-based or LBP-based methods or their combination can be used for separation and also HSV color space can be used too. Having extracted the features, the similarity criteria can be used for identification. The implementation of proposed method and its comparison with one of the newly-presented methods in this area shows better performance of the proposed method.