Classification of Polar-Thermal Eigenfaces using Multilayer Perceptron for Human Face Recognition

05/21/2010
by   Mrinal Kanti Bhowmik, et al.
0

This paper presents a novel approach to handle the challenges of face recognition. In this work thermal face images are considered, which minimizes the affect of illumination changes and occlusion due to moustache, beards, adornments etc. The proposed approach registers the training and testing thermal face images in polar coordinate, which is capable to handle complicacies introduced by scaling and rotation. Polar images are projected into eigenspace and finally classified using a multi-layer perceptron. In the experiments we have used Object Tracking and Classification Beyond Visible Spectrum (OTCBVS) database benchmark thermal face images. Experimental results show that the proposed approach significantly improves the verification and identification performance and the success rate is 97.05

READ FULL TEXT
research
07/05/2010

Human Face Recognition using Line Features

In this work we investigate a novel approach to handle the challenges of...
research
07/05/2010

Classification of Log-Polar-Visual Eigenfaces using Multilayer Perceptron

In this paper we present a simple novel approach to tackle the challenge...
research
07/05/2010

Classification of fused face images using multilayer perceptron neural network

This paper presents a concept of image pixel fusion of visual and therma...
research
07/05/2010

A Parallel Framework for Multilayer Perceptron for Human Face Recognition

Artificial neural networks have already shown their success in face reco...
research
10/21/2019

Cascaded Generation of High-quality Color Visible Face Images from Thermal Captures

Generating visible-like face images from thermal images is essential to ...
research
06/01/2017

A Vision System for Multi-View Face Recognition

Multimodal biometric identification has been grown a great attention in ...

Please sign up or login with your details

Forgot password? Click here to reset