Performance analysis for facial expression recognition under salt and pepper noise with median filter approach

Facial expression provides an important behavioural measure for studies of emotion, cognitive processes, and social interaction. Facial expression recognition has recently become a promising research area. In face recognition, the simple process of face recognition system should go through image dat...

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主要作者: Idris, Azrini
格式: Thesis
語言:English
English
English
出版: 2013
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spelling my-uthm-ep.66312022-03-10T03:42:56Z Performance analysis for facial expression recognition under salt and pepper noise with median filter approach 2013-07 Idris, Azrini TA Engineering (General). Civil engineering (General) Facial expression provides an important behavioural measure for studies of emotion, cognitive processes, and social interaction. Facial expression recognition has recently become a promising research area. In face recognition, the simple process of face recognition system should go through image data retrieval, face detection, facial feature extraction and face recognition. However, some researches focus on the part of face recognition system, such as face detection, face recognition, or algorithms dealing with certain drawbacks issues such as illumination, occlusion, noise, and angle. Thus, in this research we have considered the facial changes as represented by face emotions from JAFFE Database results for different noise levels. The proposed system consists of three modules. The first module read the images face of three different emotions such as happy, fear and surprise. Those images are flawed with different level of salt and pepper noise. Then filter is applied on the corrupted images with average and median filter. The second module constructs PCA that are responsible for feature extraction, while the third module extracts the features by processing the image and measuring dimensions of PCA using k-NN and NN. Using the proposed classifiers, some experimental results have been obtained. It is found that the highest percentage of accuracy is 71.43 % and 83.96 % for K-NN and NN classifier respectively. 2013-07 Thesis http://eprints.uthm.edu.my/6631/ http://eprints.uthm.edu.my/6631/1/24p%20AZRINI%20IDRIS.pdf text en public http://eprints.uthm.edu.my/6631/2/AZRINI%20IDRIS%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/6631/3/AZRINI%20IDRIS%20WATERMARK.pdf text en validuser mphil masters Universiti Tun Hussein Malaysia Fakulti Kejuruteraan Elektrik dan Elektronik
institution Universiti Tun Hussein Onn Malaysia
collection UTHM Institutional Repository
language English
English
English
topic TA Engineering (General)
Civil engineering (General)
spellingShingle TA Engineering (General)
Civil engineering (General)
Idris, Azrini
Performance analysis for facial expression recognition under salt and pepper noise with median filter approach
description Facial expression provides an important behavioural measure for studies of emotion, cognitive processes, and social interaction. Facial expression recognition has recently become a promising research area. In face recognition, the simple process of face recognition system should go through image data retrieval, face detection, facial feature extraction and face recognition. However, some researches focus on the part of face recognition system, such as face detection, face recognition, or algorithms dealing with certain drawbacks issues such as illumination, occlusion, noise, and angle. Thus, in this research we have considered the facial changes as represented by face emotions from JAFFE Database results for different noise levels. The proposed system consists of three modules. The first module read the images face of three different emotions such as happy, fear and surprise. Those images are flawed with different level of salt and pepper noise. Then filter is applied on the corrupted images with average and median filter. The second module constructs PCA that are responsible for feature extraction, while the third module extracts the features by processing the image and measuring dimensions of PCA using k-NN and NN. Using the proposed classifiers, some experimental results have been obtained. It is found that the highest percentage of accuracy is 71.43 % and 83.96 % for K-NN and NN classifier respectively.
format Thesis
qualification_name Master of Philosophy (M.Phil.)
qualification_level Master's degree
author Idris, Azrini
author_facet Idris, Azrini
author_sort Idris, Azrini
title Performance analysis for facial expression recognition under salt and pepper noise with median filter approach
title_short Performance analysis for facial expression recognition under salt and pepper noise with median filter approach
title_full Performance analysis for facial expression recognition under salt and pepper noise with median filter approach
title_fullStr Performance analysis for facial expression recognition under salt and pepper noise with median filter approach
title_full_unstemmed Performance analysis for facial expression recognition under salt and pepper noise with median filter approach
title_sort performance analysis for facial expression recognition under salt and pepper noise with median filter approach
granting_institution Universiti Tun Hussein Malaysia
granting_department Fakulti Kejuruteraan Elektrik dan Elektronik
publishDate 2013
url http://eprints.uthm.edu.my/6631/1/24p%20AZRINI%20IDRIS.pdf
http://eprints.uthm.edu.my/6631/2/AZRINI%20IDRIS%20COPYRIGHT%20DECLARATION.pdf
http://eprints.uthm.edu.my/6631/3/AZRINI%20IDRIS%20WATERMARK.pdf
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