Adaptive Threshold Gesture Segmentation Algorithm Based on Skin Color

DOI

10.2991/ameii-16.2016.301How to use a DOI?

Keywords

Gesture recognition, Gaussian model, Skin segmentation, Otsu algorithm

Abstract

In gesture recognition systems, segmenting gestures from complex background is the hardest and the most critical part. Gesture segmentation is the prerequisite of following image processing, and the result of segmentation has a direct influence on the result of gesture recognition. This paper proposed an algorithm of adaptive threshold gesture segmentation based on skin color. First of all, a whole image should be transformed from RGB color space to YCbCr color space. After eliminating luminance component Y, similarity graph of skin color will be obtained from the already established Gaussian model. Then Otsu adaptive threshold algorithm is used to carry out binary processing for the similarity graph of skin color. After the segmentation of skin color regions, the morphology method is used to process binary image for determining the location of hands. Experimental results show that the detailed segmentation of skin color using the dynamic-adaptive threshold can improve noise resistance and can produce better results.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Chengyuan Liu
AU  - Jingqiu Wang
AU  - Ting Zhang
AU  - Dongsheng Ding
PY  - 2016/04
DA  - 2016/04
TI  - Adaptive Threshold Gesture Segmentation Algorithm Based on Skin Color
BT  - Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016)
PB  - Atlantis Press
SN  - 2352-5401
UR  - https://doi.org/10.2991/ameii-16.2016.301
DO  - 10.2991/ameii-16.2016.301
ID  - Liu2016/04
ER  -