K-Means approach to facial expressions recognition

A method is proposed to recognize facial expressions. The method used two simple features to recognize the expressions which are the density of pixels and the ratio of height to width of cropped boundary regions. The system first applies some preprocessing stages to enhance the input image and reduc...

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Main Authors: Zeki, Ahmed M., Serda Ali, Ruzanna, Appalasamy, Patma
Format: Proceeding Paper
Language:English
Published: 2012
Subjects:
Online Access:http://irep.iium.edu.my/29169/
http://irep.iium.edu.my/29169/1/K-Means_Approach_to_Facial_Expressions.pdf
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author Zeki, Ahmed M.
Serda Ali, Ruzanna
Appalasamy, Patma
author_facet Zeki, Ahmed M.
Serda Ali, Ruzanna
Appalasamy, Patma
author_sort Zeki, Ahmed M.
building IIUM Repository
collection Online Access
description A method is proposed to recognize facial expressions. The method used two simple features to recognize the expressions which are the density of pixels and the ratio of height to width of cropped boundary regions. The system first applies some preprocessing stages to enhance the input image and reduce the noise. The face boundary will then be detected. The region of interest (i.e. mouth and eyes) will be determined, from which, features will be extracted. Finally based on the features extracted, the face will be classified into one of three different classes using the K-means method. The method was applied and tested on a dataset of 200 images of faces and the success rate obtained was 76.5%.
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format Proceeding Paper
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institution International Islamic University Malaysia
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language English
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publishDate 2012
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spelling iium-291692013-04-02T02:42:20Z http://irep.iium.edu.my/29169/ K-Means approach to facial expressions recognition Zeki, Ahmed M. Serda Ali, Ruzanna Appalasamy, Patma QA75 Electronic computers. Computer science A method is proposed to recognize facial expressions. The method used two simple features to recognize the expressions which are the density of pixels and the ratio of height to width of cropped boundary regions. The system first applies some preprocessing stages to enhance the input image and reduce the noise. The face boundary will then be detected. The region of interest (i.e. mouth and eyes) will be determined, from which, features will be extracted. Finally based on the features extracted, the face will be classified into one of three different classes using the K-means method. The method was applied and tested on a dataset of 200 images of faces and the success rate obtained was 76.5%. 2012 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/29169/1/K-Means_Approach_to_Facial_Expressions.pdf Zeki, Ahmed M. and Serda Ali, Ruzanna and Appalasamy, Patma (2012) K-Means approach to facial expressions recognition. In: 2012 International Conference on Information Technology and e-Services, 24-26 March 2012, Sousse, Tunisia.
spellingShingle QA75 Electronic computers. Computer science
Zeki, Ahmed M.
Serda Ali, Ruzanna
Appalasamy, Patma
K-Means approach to facial expressions recognition
title K-Means approach to facial expressions recognition
title_full K-Means approach to facial expressions recognition
title_fullStr K-Means approach to facial expressions recognition
title_full_unstemmed K-Means approach to facial expressions recognition
title_short K-Means approach to facial expressions recognition
title_sort k-means approach to facial expressions recognition
topic QA75 Electronic computers. Computer science
url http://irep.iium.edu.my/29169/
http://irep.iium.edu.my/29169/1/K-Means_Approach_to_Facial_Expressions.pdf