Face recognition using illumination-invariant local patches

Illumination variation that span globally and locally across the facial surface is one of the most important aspect in designing a robust face recognition system. The illumination variations due to changes in lighting conditions could produce different shape of shading on the face thus deforming th...

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Main Authors:	Shafie, Amir Akramin, Hafiz, Fadhlan, Mohd Mustafah, Yasir
Format:	Conference or Workshop Item
Language:	English English English
Published:	2014
Subjects:	T Technology (General)
Online Access:	http://irep.iium.edu.my/41699/ http://irep.iium.edu.my/41699/ http://irep.iium.edu.my/41699/1/Face_Recognition_Using_Illumination-Invariant_Local_Patches.pdf http://irep.iium.edu.my/41699/4/ICIAS_2014_-_COVER.pdf http://irep.iium.edu.my/41699/7/41699_Face%20recognition%20using_Scopus.pdf

id	iium-41699
recordtype	eprints
spelling	iium-416992017-09-07T03:08:35Z http://irep.iium.edu.my/41699/ Face recognition using illumination-invariant local patches Shafie, Amir Akramin Hafiz, Fadhlan Mohd Mustafah, Yasir T Technology (General) Illumination variation that span globally and locally across the facial surface is one of the most important aspect in designing a robust face recognition system. The illumination variations due to changes in lighting conditions could produce different shape of shading on the face thus deforming the facial features. The effect of these variations is simply more severe in the presence of single-sample constraint since there would be many variables with very limited observations. Illumination variations have been modelled in literature as a series of undetermined multiplicative and additive noise, hence it is more convenient to eliminate or reduce the effect rather than computing them. In this paper, we present an illumination-invariant method where we use local features as basis for face classification which is obtained from partitioning histogram-equalized faces into smaller overlapping local patches (LPs). We can achieve illumination-invariance for these LPs by subtracting the vectors with local average illumination and then these vectors are logarithmically normalized to enhance the local contrast. The degree of invariance is controlled by a weight connected to the average intensity component. We have tested this method in single sample face recognition setting on AR Database and Extended YALE B Database. Recognition results show that the proposed method is suitable for robust face recognition since it achieve good performance in both even illumination and uneven illumination cases. 2014 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/41699/1/Face_Recognition_Using_Illumination-Invariant_Local_Patches.pdf application/pdf en http://irep.iium.edu.my/41699/4/ICIAS_2014_-_COVER.pdf application/pdf en http://irep.iium.edu.my/41699/7/41699_Face%20recognition%20using_Scopus.pdf Shafie, Amir Akramin and Hafiz, Fadhlan and Mohd Mustafah, Yasir (2014) Face recognition using illumination-invariant local patches. In: 2014 5th International Conference on Intelligent and Advanced Systems (ICIAS 2014), 3-5 June 2014, Kuala Lumpur Convention Center (KLCC), Kuala Lumpur. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6869544&punumber%3D6862971%26sortType%3Dasc_p_Sequence%26filter%3DAND%28p_IS_Number%3A6869438%29%26pageNumber%3D5
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English English
topic	T Technology (General)
spellingShingle	T Technology (General) Shafie, Amir Akramin Hafiz, Fadhlan Mohd Mustafah, Yasir Face recognition using illumination-invariant local patches
description	Illumination variation that span globally and locally across the facial surface is one of the most important aspect in designing a robust face recognition system. The illumination variations due to changes in lighting conditions could produce different shape of shading on the face thus deforming the facial features. The effect of these variations is simply more severe in the presence of single-sample constraint since there would be many variables with very limited observations. Illumination variations have been modelled in literature as a series of undetermined multiplicative and additive noise, hence it is more convenient to eliminate or reduce the effect rather than computing them. In this paper, we present an illumination-invariant method where we use local features as basis for face classification which is obtained from partitioning histogram-equalized faces into smaller overlapping local patches (LPs). We can achieve illumination-invariance for these LPs by subtracting the vectors with local average illumination and then these vectors are logarithmically normalized to enhance the local contrast. The degree of invariance is controlled by a weight connected to the average intensity component. We have tested this method in single sample face recognition setting on AR Database and Extended YALE B Database. Recognition results show that the proposed method is suitable for robust face recognition since it achieve good performance in both even illumination and uneven illumination cases.
format	Conference or Workshop Item
author	Shafie, Amir Akramin Hafiz, Fadhlan Mohd Mustafah, Yasir
author_facet	Shafie, Amir Akramin Hafiz, Fadhlan Mohd Mustafah, Yasir
author_sort	Shafie, Amir Akramin
title	Face recognition using illumination-invariant local patches
title_short	Face recognition using illumination-invariant local patches
title_full	Face recognition using illumination-invariant local patches
title_fullStr	Face recognition using illumination-invariant local patches
title_full_unstemmed	Face recognition using illumination-invariant local patches
title_sort	face recognition using illumination-invariant local patches
publishDate	2014
url	http://irep.iium.edu.my/41699/ http://irep.iium.edu.my/41699/ http://irep.iium.edu.my/41699/1/Face_Recognition_Using_Illumination-Invariant_Local_Patches.pdf http://irep.iium.edu.my/41699/4/ICIAS_2014_-_COVER.pdf http://irep.iium.edu.my/41699/7/41699_Face%20recognition%20using_Scopus.pdf
first_indexed	2023-09-18T20:59:38Z
last_indexed	2023-09-18T20:59:38Z
_version_	1777410536684650496

Face recognition using illumination-invariant local patches

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