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Edge-Based Facial Feature Extraction using Adaptive Canny Operator Edge Detection

http://hdl.handle.net/20.500.12678/0000004512
195f85f3-1a96-4196-bd8c-65ed6a16c782
34782076-4665-4549-9e26-95a85f6328ca
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Publication
Title
Title Edge-Based Facial Feature Extraction using Adaptive Canny Operator Edge Detection
Language en_US
Publication date 2012-02-28
Authors
Aung, Darli Myint
Description
Facial feature extraction is an essential stepin the face detection and facial expressionrecognition frameworks. To develop a betterfacial expression recognition system, a goodfeature extraction method is needed. In thispaper, an efficient Facial Feature Extractionmethod for recognizing four different expressionssuch as neutral, happy, surprise and sad ispresented. In this study, adaptive canny operatoredge detection method is used to reduce thecomputational complexity and improved theaccuracy of feature point location. To validatethe performance of the proposed featureextraction, the generated features are classifiedusing Maximum Correlation Classifier (MCC).The experimental results demonstrated that theproposed feature extraction method couldgenerate significant facial features and thesefeatures are able to be classified into eachexpression. Our results also showed that theproposed feature extraction method is moreefficient than Gabor wavelet edge detectionmethod.
Keywords
Adaptive Canny Operator Edge Detection, Facial Feature Extraction, Maximum Correlation Classifier, Gabar Wavelet edge detection method
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/2438
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