Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Vol 7, No 4: December 2019

Evaluation and Applying Feature Extraction Techniques for Face Detection and Recognition

Arokia Paul Rajan (Associate Professor)
Angel Rose Mathew (Unknown)



Article Info

Publish Date
02 Jan 2020

Abstract

Detecting the image and identifying the face has become important in the field of computer vision for recognizing and analyzing, reconstructing into 3D, and labelling the image. Feature extraction is usually the first stage in detection and recognition of the image processing and computer vision. It supports the conversion of the image into a quantitative data. Later, this converted data can be used for labelling, classifying and recognizing a model. In this paper, performance of such feature extraction techniques viz. Local Binary Pattern (LBP), Histogram of Oriented Gradients (HOG) and Convolutional Neural Network (CNN) technique is applied to detect and recognize the face. The experiments conducted with a data set addressing the issues like pose variation, facial expression and intensity of light. The efficiency of the algorithms were evaluated based on the computational time and accuracy rate.

Copyrights © 2019






Journal Info

Abbrev

IJEEI

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is a peer reviewed International Journal in English published four issues per year (March, June, September and December). The aim of Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is to publish high-quality ...