Sign In
Register
eISSN:2278-5299

International Journal of Latest Research in Science and Technology

DOI:10.29111/ijlrst   ISRA Impact Factor:3.35

A News Letter Sign UP!
GESTURE SEGMENTATION USING AN ADAPTIVE THRESHOLD ALGORITHM

Research Paper Open Access

International Journal of Latest Research in Science and Technology Vol.3 Issue 4, pp 65-71,Year 2014

GESTURE SEGMENTATION USING AN ADAPTIVE THRESHOLD ALGORITHM

Mei Wang, Jzau-Sheng Lin, Zhou Xing Fu,Guo Qing Meng

Correspondence should be addressed to :

Received : 15 August 2014; Accepted : 26 August 2014 ; Published : 31 August 2014

Share
Download 125
View 177
Article No. 10356
Abstract

Hand gesture segmentation is a key step for gesture recognition. Based on the construction of a new color space of skin model, a new dynamic-thresholding segmentation approach named Adaptive Threshold Segmentation Algorithm (ATSA) was further developed and segmentation effect evaluation was conducted. Some images of hand gesture were processed by using ATSA and the Fixed Threshold Segmentation (FTS) algorithm as well as the Similarity algorithm of Skin Color (SSC). Comparing with FTS and SSC algorithms, The ATSA is experimentally demonstrated that, the segmentation results have a less brightness impact, a lower redundancy rate, a lower rate of false alarm and missing, and a higher integrity rate.

Key Words   
Image Segmentation; Adaptive Threshold, Hand Gesture

Copyright
References
  1. Guan, R. and Xu, X. M., “A computer vision-based gesture detection and recognition technique,” Computer Applications and Soft-ware. 30, pp. 155-164, 2013.
  2. Choi, J., Park, J., Park, H., and Park, J, “iHand: an interactive bare-hand-based augmented reality interface on commercial mobile phones,” Opt. Eng. 52, 027206 [doi: 10.1117/1.OE. 52.2.027206], 2013.
  3. Liu, J. M. and Yuan Q. Q., “A new method of hand gesture segmentation with complex backgrounds,” Journal of Beijing Electronic Science and Technology Institute. 14, pp. 23-27, 2006.
  4. Nolker, C. and Ritter, H., “Visual recognition of continuous hand postures,” IEEE Trans. on Neural Networks. 13, pp. 983-994, 2002.
  5. Pradhan, G., Prabhakaran, B., and Li, C. J., “Hand-gesture computing for the hearing and speech impaired,” IEEE Trans. on MultiMedia. 15, pp. 20-27, 2008.
  6. Rafael, B., Miguel, S. D, and Miguel, S., “Skin color profile capture for scale and rotation invariant hand gesture recognition,” Lectures Notes in Computer Science. 5085, pp. 81-92, 2009.
  7. Ankit, A. B. and Sanjay, N. T., “Vision-based Authenticated Robotic Control using Face and Hand Gesture Recognition,” Proceeding on the 3rd International Conf. of Electronics Computer Technology, pp. 64-68, 2011.
  8. Dawod, A. Y., Abdullah, J., and Alam, M. J., “ Adaptive skin color model for hand segmentation,” Int. Conf. on Computer Applications and Industrial Electronics, pp. 486-489, 2010.
  9. Ma, G. Y. and Liu, X. Y., “ Operational gesture segmentation and recognition,” Tsinghua Science and Technology,. 8, pp. 169-173, 2003.
  10. Gupta, L. and Ma, S. W., “Gesture-based interaction and communication: automated classification of hand gesture contours,” IEEE Trans. on Systems, Man, and Cybernetics, Part C: Applications and Reviews. 31, pp. 114-120, 2001.
  11. Li, C. M., Huang,  ,  Ding, Z. H., Gatenby, J. C., Metaxas, D. N., and Gore , J. C., “A level set method for image segmentation in the presence of intensity in homogeneities with application to MRI,”. IEEE Trans. on Image Processing. 20, pp. 2007 – 2016, 2011.
  12. Yang, D. G., Wan, H. J., and Yang, M., “Natural image segmentation based on contour detection,” Journal of Huazhong Normal University (Natural Sciences).46, pp. 18-21, 2012.
  13. Schwarz, L. A., Mkhitaryan, and A., Mateus, D., “Estimating human 3D pose from time-of-flight images based on geodesic distances and optical flow,” Proceeding on IEEE Int. Conf. of Automatic Face & Gesture Recognition and Workshops, pp. 700-706, 2011.
  14. Unnikrishnan, R., Pantofaru, C., and Hebert, M., “Toward objective evaluation of image segmentation algorithms,” IEEE Trans. on Pattern Analysis and Machine Intelligence, 29, pp. 929-94, 2007.
  15. Park, J. G. and Lee, C., “Bayesian rule-based complex background modeling and foreground detection,” Optical Eng. 49, [doi: 10.1117/1.3319820], 2010.
  16. Dardas, N., Georganas, H., and Nicolas, D., “Real-time hand gesture detection and recognition using bag-of-features and support vector machine techniques,” IEEE Trans. on Instrumentation and Measurement. 60, pp. 3592-3607, 2011.
  17. Suppatoomsin, C., “Hybrid method for hand segmentation,” Proc. SPIE 7546. [doi: 10.1117/12.856290], 2010.
  18. Lu, K., Li, X. J., and Zhou, J. X., “Hand signal recognition based on skin color and edge outline examination,” J. of North China University of Technology,” Beijing China. 18, pp. 12-15,2006.
  19. Guo, S., Gu, G. C., and Cai, Z. S., “Skin segmentation using similarity of skin color and dynamic threshold,” Computer Engineering and Applications, 46, pp. 1-3, 2010.
  20. Zheng, Y. W., Feng, Z. Q., Yang, B., and Xu, T., “The research of gesture feature extraction algorithm based on the vector edge detection,” China academic journal electronic publishing house, http://www.cnki.net, 2010.
To cite this article

Mei Wang, Jzau-Sheng Lin, Zhou Xing Fu,Guo Qing Meng , " Gesture Segmentation Using An Adaptive Threshold Algorithm ", International Journal of Latest Research in Science and Technology . Vol. 3, Issue 4, pp 65-71 , 2014

Responsive image

MNK Publication was founded in 2012 to upholder revolutionary ideas that would advance the research and practice of business and management. Today, we comply with to advance fresh thinking in latest scientific fields where we think we can make a real difference and growth now also including medical and social care, education,management and engineering.

Responsive image

We offers several opportunities for partnership and tie-up with individual, corporate and organizational level. We are working on the open access platform. Editors, authors, readers, librarians and conference organizer can work together. We are giving open opportunities to all. Our team is always willing to work and collaborate to promote open access publication.

Responsive image

Our Journals provide one of the strongest International open access platform for research communities. Our conference proceeding services provide conference organizers a privileged platform for publishing extended conference papers as journal publications. It is deliberated to disseminate scientific research and to establish long term International collaborations and partnerships with academic communities and conference organizers.