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Facial emotion recognition based on empirical mode decomposition and discrete wavelet transform analysis

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cris.author.scopus-author-id 57218540740
cris.author.scopus-author-id 26655536100
cris.author.scopus-author-id 57008126300
cris.author.scopus-author-id 57202286808
cris.author.scopus-author-id 56441236100
cris.author.scopus-author-id 57200576499
dc.contributor.author Ali H.
dc.contributor.author Hariharan M.
dc.contributor.author Mansor H.
dc.contributor.author Adenan S.N.
dc.contributor.author Elshaikh M.
dc.contributor.author Wan K.
dc.date.accessioned 2025-01-13T07:42:43Z
dc.date.available 2025-01-13T07:42:43Z
dc.date.issued 2018-01-01
dc.description.abstract This paper presents a new framework of using empirical mode decomposition (EMD) and discrete wavelet transform (DWT) with an application for facial emotion recognition. EMD is a multi-resolution technique used to decompose any complicated signal into a small set of intrinsic mode functions (IMFs) based on sifting process. In this framework, the EMD was applied on facial images to extract the informative features by decomposing the image into a set of IMFs and residue. The selected IMFs was then subjected to DWT in which it decomposes the instantaneous frequency of the IMFs into four sub band. The approximate coefficients (cA1) at first level decomposition are extracted and used as significant features to recognize the facial emotion. Since there are a large number of coefficients, hence the principal component analysis (PCA) is applied to the extracted features. The k-nearest neighbor classifier is adopted as a classifier to classify seven facial emotions (anger, disgust, fear, happiness, neutral, sadness and surprise). To evaluate the effectiveness of the proposed method, the JAFFE database has been employed. Based on the results obtained, the proposed method demonstrates the recognition rate of 80.28%, thus it is converging.
dc.identifier.scopus 2-s2.0-85047763239
dc.identifier.uri https://hdl.handle.net/20.500.14170/11801
dc.relation.grantno undefined
dc.relation.ispartof Journal of Telecommunication, Electronic and Computer Engineering
dc.relation.ispartofseries Journal of Telecommunication, Electronic and Computer Engineering
dc.relation.issn 21801843
dc.subject Discrete Wavelet Transform | Empirical Mode Decomposition | Facial Emotion Recognition | K-Nearest Neighbour | PCA
dc.title Facial emotion recognition based on empirical mode decomposition and discrete wavelet transform analysis
dc.type Journal
dspace.entity.type Publication
oaire.citation.endPage 41
oaire.citation.issue 1-13
oaire.citation.startPage 37
oaire.citation.volume 10
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
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person.identifier.scopus-author-id 57218540740
person.identifier.scopus-author-id 26655536100
person.identifier.scopus-author-id 57008126300
person.identifier.scopus-author-id 57202286808
person.identifier.scopus-author-id 56441236100
person.identifier.scopus-author-id 57200576499
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