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Facial Feature Extraction Based on Wavelet Transform

  • Conference paper
Artificial Intelligence and Computational Intelligence (AICI 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5855))

Abstract

Facial feature extraction is one of the most important processes in face recognition, expression recognition and face detection. The aims of facial feature extraction are eye location, shape of eyes, eye brow, mouth, head boundary, face boundary, chin and so on. The purpose of this paper is to develop an automatic facial feature extraction system, which is able to identify the eye location, the detailed shape of eyes and mouth, chin and inner boundary from facial images. This system not only extracts the location information of the eyes, but also estimates four important points in each eye, which helps us to rebuild the eye shape. To model mouth shape, mouth extraction gives us both mouth location and two corners of mouth, top and bottom lips. From inner boundary we obtain and chin, we have face boundary. Based on wavelet features, we can reduce the noise from the input image and detect edge information. In order to extract eyes, mouth, inner boundary, we combine wavelet features and facial character to design these algorithms for finding midpoint, eye’s coordinates, four important eye’s points, mouth’s coordinates, four important mouth’s points, chin coordinate and then inner boundary. The developed system is tested on Yale Faces and Pedagogy student’s faces.

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Author information

Authors and Affiliations

  1. Department of Mathematics and Computer Science, University of Pedagogy, Ho Chi Minh City, Viet Nam

    Nguyen Viet Hung

Authors
  1. Nguyen Viet Hung
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Editor information

Editors and Affiliations

  1. School of Business Information Technology, RMIT University, City Campus, 124 La Trobe Street, 3000, Melbourne, Victoria, Australia

    Hepu Deng

  2. College of Metrological Technology and Engineering, China Jiliang University, 310018, Hangzhou, Zhejiang Province, China

    Lanzhou Wang

  3. Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong, Hong Kong, China

    Fu Lee Wang

  4. College of Information Science and Technology, Hainan University, 570228, Haikou, China

    Jingsheng Lei

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© 2009 Springer-Verlag Berlin Heidelberg

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Hung, N.V. (2009). Facial Feature Extraction Based on Wavelet Transform. In: Deng, H., Wang, L., Wang, F.L., Lei, J. (eds) Artificial Intelligence and Computational Intelligence. AICI 2009. Lecture Notes in Computer Science(), vol 5855. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05253-8_37

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  • DOI: https://doi.org/10.1007/978-3-642-05253-8_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-05252-1

  • Online ISBN: 978-3-642-05253-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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