DeepQ Residue Analysis of Computer Vision Dataset using Support Vector Machine – Journal of Internet Services and Information Security

Volume 13 - Issue 1

DeepQ Residue Analysis of Computer Vision Dataset using Support Vector Machine

Rahama Salman Lecturer, Department of Information Technology and Security, College of Computer Science and Information Technology Jazan University, Jazan, Kingdom of Saudi Arabia.
rabdol@jazanu.edu.sa 0000-0003-4105-5019
Arshia Arjumand Banu Lecturer, Department of Computer Science, College of Computer Science and Information Technology, Jazan University, Jazan, Kingdom of Saudi Arabia.
abanu@jazanu.edu.sa 0009-0009-7000-3809

DOI: 10.58346/JISIS.2023.I1.008

Keywords: Face Detection; KNN Classifier, Computer Vision Dataset, Support Vector Machine, Deep Learning, Residue Analysis

Abstract

A vision-based human computer interface is used to automatically recognize human mood. Image processing techniques used include a web camera for eye detection. Appearance tracking method (ABT) is measured face identification and K means Nearest Neighbor (K-NN) is used for eye detection. DWT - Discrete Wavelet Transform and DCT - Discrete Cosine Transform are suitable to extract features of eye and SVM is used to classify eye expressions. Classification of eye expressions includes anger, fear, happiness, disgust, neutral and sad. Experimental results confirm that the proposed method recognized facial expressions with higher accuracy.

Date

February 2023

Page Number

78-84