FPGA based Real Time Human Hand Gesture Recognition System

Abstract This work proposes a real time human hand gesture recognition system for human computer interaction. The proposed system can recognize 10 different hand gestures at faster rate with reasonable accuracy. The gestures are classified on the basis of shape-based features. Four different shape based features are used for better accuracy. The illumination compensation technique is employed for robust recognition under varying background lightning conditions. Skin color segmentation is used to minimize the chances of false detection. The proposed system is modeled using Verilog HDL and targeted for Xillinx Virtex2 Pro FPGA board. The accuracy of the system is computed as 94.40%.

[1]  Nanfeng Xiao,et al.  Improved RCE neural network and its application in human-robot interaction based on hand gesture recognition , 2010, The 2nd International Conference on Information Science and Engineering.

[2]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[3]  R. Engelbrecht,et al.  DIGEST of TECHNICAL PAPERS , 1959 .

[4]  Anupam Agrawal,et al.  Interaction with virtual game through hand gesture recognition , 2011, 2011 International Conference on Multimedia, Signal Processing and Communication Technologies.

[5]  Toshiaki Kondo,et al.  A simple shape-based approach to hand gesture recognition , 2010, ECTI-CON2010: The 2010 ECTI International Confernce on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology.

[6]  Masumi Ishikawa,et al.  Recognition of a hand-gesture based on self-organization using a DataGlove , 1999, ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378).

[7]  Bülent Sankur,et al.  Shape-based hand recognition , 2006, IEEE Transactions on Image Processing.

[8]  Kwanghoon Sohn,et al.  Illumination invariant skin color segmentation , 2009, 2009 4th IEEE Conference on Industrial Electronics and Applications.

[9]  Yu Shi,et al.  An FPGA-based Smart Camera for Gesture Analysis for Healthcare Applications , 2008, 2008 Digest of Technical Papers - International Conference on Consumer Electronics.

[10]  Cheng Lu,et al.  On the removal of shadows from images , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Lalit Gupta,et al.  Gesture-based interaction and communication: automated classification of hand gesture contours , 2001, IEEE Trans. Syst. Man Cybern. Syst..

[12]  S. L. Phung,et al.  A novel skin color model in YCbCr color space and its application to human face detection , 2002, Proceedings. International Conference on Image Processing.

[13]  Chen-Chiung Hsieh,et al.  A real time hand gesture recognition system using motion history image , 2010, 2010 2nd International Conference on Signal Processing Systems.