On a Feature Extraction by LMCUH Algorithm for a Ubiquitous Computing

  • Jin Ok Kim
  • Jun Yeong Jang
  • Chin Hyun Chung
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3980)


This paper proposes an algorithm to detect human faces under various environments. In the first step, information on three color spaces of various features is used to determine histogram of color in the first frame of an image. The histogram obtained by interpolation after combining three color of the image is used as an input of LMCUH network. In the second step, the neural network of Levenberg – Marquadt training algorithm minimizes the error. Next, we find the face in test image by using the trained sets. This method is especially suited for various scales, rotations, lighting levels, or occlusions of the target image. Experimental results show that two – dimensional images of a face can be effectively implemented by using artificial neural network training under various environments. Thus, we can detect the face effectively and this can inevitably lead to the Ubiquitous Computing Environment.


Skin Color Face Image Face Detection Ubiquitous Computing Color Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jin Ok Kim
    • 1
  • Jun Yeong Jang
    • 2
  • Chin Hyun Chung
    • 2
  1. 1.Faculty of MultimediaDaegu Haany UniversityGyeongsangbuk-doKorea
  2. 2.Department of Information and Control EngineeringKwangwoon UniversitySeoulKorea

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