A Restricted Coulomb Energy (RCE) Neural Network System for Hand Image Segmentation

A hands segmentation scheme based on human skin color classification using the Restricted Coulomb Energy (RCE) neural network is proposed in this paper. An improved iteration strategy for the RCE neural network, with a reduction in the number of repetitive calculations, is utilized in our work. The experimental results show that our system is more accurate and less computational expensive than previous schemes.

[1]  Surendra Ranganath,et al.  Real-time gesture recognition system and application , 2002, Image Vis. Comput..

[2]  Ming Xie,et al.  Hand image segmentation using color and RCE neural network , 2001, Robotics Auton. Syst..

[3]  Jing Li Wang,et al.  Color image segmentation: advances and prospects , 2001, Pattern Recognit..

[4]  Chia-Feng Juang,et al.  A Self-Organizing TS-Type Fuzzy Network With Support Vector Learning and its Application to Classification Problems , 2007, IEEE Transactions on Fuzzy Systems.

[5]  Richard Bowden,et al.  A boosted classifier tree for hand shape detection , 2004, Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings..

[6]  Pengfei Shi,et al.  A new segmentation approach for iris recognition based on hand-held capture device , 2007, Pattern Recognit..

[7]  Q. P. Ha,et al.  Effect of Color Space on Color Image Segmentation , 2009, 2009 2nd International Congress on Image and Signal Processing.

[8]  Tamás Szirányi,et al.  User-adaptive hand gesture recognition system with interactive training , 2005, Image Vis. Comput..

[9]  Ying Wu,et al.  Nonstationary color tracking for vision-based human-computer interaction , 2002, IEEE Trans. Neural Networks.

[10]  Ming Xie,et al.  Finger identification and hand posture recognition for human-robot interaction , 2007, Image Vis. Comput..

[11]  Mircea Nicolescu,et al.  Vision-based hand pose estimation: A review , 2007, Comput. Vis. Image Underst..

[12]  Thierry Carron,et al.  Color edge detector using jointly hue, saturation and intensity , 1994, Proceedings of 1st International Conference on Image Processing.

[13]  Ying Wu,et al.  View-independent recognition of hand postures , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[14]  Alexander Zelinsky,et al.  MAP ZDF segmentation and tracking using active stereo vision: Hand tracking case study , 2007, Comput. Vis. Image Underst..

[15]  Ho-Sub Yoon,et al.  Gesture-based editing system for graphic primitives and alphanumeric characters , 1999 .

[16]  Mathias Kölsch,et al.  Robust hand detection , 2004, Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings..

[17]  J.-H. Lee,et al.  Comparison of colour transformations for image segmentation , 1994 .

[18]  Ming Xie,et al.  Color clustering and learning for image segmentation based on neural networks , 2005, IEEE Trans. Neural Networks.

[19]  Christine Connolly,et al.  A study of efficiency and accuracy in the transformation from RGB to CIELAB color space , 1997, IEEE Trans. Image Process..

[20]  John M. Gauch,et al.  Comparison of three-color image segmentation algorithms in four color spaces , 1992, Other Conferences.

[21]  Charles A. Poynton,et al.  A technical introduction to digital video , 1996 .