Improving the Component-Based Face Recognition Using Enhanced Viola–Jones and Weighted Voting Technique
This paper enhances the recognition capabilities of the facial component-based techniques using the concepts of better Viola–Jones component detection and weighting facial components. Our method starts with enhanced Viola–Jones face component detection and cropping. The facial components are detecte...
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2019-01-01
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Series: | Modelling and Simulation in Engineering |
Online Access: | http://dx.doi.org/10.1155/2019/8234124 |
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doaj-cf12a413b8a945e5bf0c06e3eec36d362020-11-24T21:48:19ZengHindawi LimitedModelling and Simulation in Engineering1687-55911687-56052019-01-01201910.1155/2019/82341248234124Improving the Component-Based Face Recognition Using Enhanced Viola–Jones and Weighted Voting TechniqueIssam Dagher0Hussein Al-Bazzaz1University of Balamand, Department of Computer Engineering, El-Koura, LebanonUniversity of Balamand, Department of Computer Engineering, El-Koura, LebanonThis paper enhances the recognition capabilities of the facial component-based techniques using the concepts of better Viola–Jones component detection and weighting facial components. Our method starts with enhanced Viola–Jones face component detection and cropping. The facial components are detected and cropped accurately during all pose-changing circumstances. The cropped components are represented by the histogram of oriented gradients (HOG). The weight of each component was determined using a validation process. Combining these weights was done by a simple voting technique. Three public databases were used: the AT&T database, the PUT database, and the AR database. Several improvements are observed using the weighted voting recognition method presented in this paper.http://dx.doi.org/10.1155/2019/8234124 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Issam Dagher Hussein Al-Bazzaz |
spellingShingle |
Issam Dagher Hussein Al-Bazzaz Improving the Component-Based Face Recognition Using Enhanced Viola–Jones and Weighted Voting Technique Modelling and Simulation in Engineering |
author_facet |
Issam Dagher Hussein Al-Bazzaz |
author_sort |
Issam Dagher |
title |
Improving the Component-Based Face Recognition Using Enhanced Viola–Jones and Weighted Voting Technique |
title_short |
Improving the Component-Based Face Recognition Using Enhanced Viola–Jones and Weighted Voting Technique |
title_full |
Improving the Component-Based Face Recognition Using Enhanced Viola–Jones and Weighted Voting Technique |
title_fullStr |
Improving the Component-Based Face Recognition Using Enhanced Viola–Jones and Weighted Voting Technique |
title_full_unstemmed |
Improving the Component-Based Face Recognition Using Enhanced Viola–Jones and Weighted Voting Technique |
title_sort |
improving the component-based face recognition using enhanced viola–jones and weighted voting technique |
publisher |
Hindawi Limited |
series |
Modelling and Simulation in Engineering |
issn |
1687-5591 1687-5605 |
publishDate |
2019-01-01 |
description |
This paper enhances the recognition capabilities of the facial component-based techniques using the concepts of better Viola–Jones component detection and weighting facial components. Our method starts with enhanced Viola–Jones face component detection and cropping. The facial components are detected and cropped accurately during all pose-changing circumstances. The cropped components are represented by the histogram of oriented gradients (HOG). The weight of each component was determined using a validation process. Combining these weights was done by a simple voting technique. Three public databases were used: the AT&T database, the PUT database, and the AR database. Several improvements are observed using the weighted voting recognition method presented in this paper. |
url |
http://dx.doi.org/10.1155/2019/8234124 |
work_keys_str_mv |
AT issamdagher improvingthecomponentbasedfacerecognitionusingenhancedviolajonesandweightedvotingtechnique AT husseinalbazzaz improvingthecomponentbasedfacerecognitionusingenhancedviolajonesandweightedvotingtechnique |
_version_ |
1725892887835574272 |