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New Fuzzy Skin Model for Face Detection

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AI 2005: Advances in Artificial Intelligence (AI 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3809))

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Abstract

We discuss the face detection method by using skin information. Skin color has proven to be a useful and robust cue for face detection, localization and tracking. Numerous techniques for skin color modelling and recognition have been proposed during several past years. In this paper we propose a new fuzzy skin model for face detection and its identification method. The fuzzy skin model comprise of the fuzzy rules with color information. The membership function and structure of fuzzy rule are identified by the proposed linear matrix inequality method. Experimental results demonstrate successful face detection.

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Author information

Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, Yonsei University, Seodaemun-gu, Seoul, 120-749, Korea

    Moon Hwan Kim & Jin Bae Park

  2. School of Electronic and Information Engineering, Kunsan National University, Kunsan, Chonbuk, 573-701, Korea

    Young Hoon Joo

Authors
  1. Moon Hwan Kim
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  2. Jin Bae Park
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  3. Young Hoon Joo
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Editor information

Editors and Affiliations

  1. Guangxi Normal University, College of CS and IT, Guilin, China, and University of Technology, Faculty of Engineering and Information Technology, Sydney, Australia

    Shichao Zhang

  2. Department of Electrical and Computer Systems Engineering, Monash University, 3800, Melbourne, Victoria, Australia

    Ray Jarvis

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© 2005 Springer-Verlag Berlin Heidelberg

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Kim, M.H., Park, J.B., Joo, Y.H. (2005). New Fuzzy Skin Model for Face Detection. In: Zhang, S., Jarvis, R. (eds) AI 2005: Advances in Artificial Intelligence. AI 2005. Lecture Notes in Computer Science(), vol 3809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11589990_58

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  • DOI: https://doi.org/10.1007/11589990_58

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30462-3

  • Online ISBN: 978-3-540-31652-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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