Adaptive Threshold Gesture Segmentation Algorithm Based on Skin Color
- 10.2991/ameii-16.2016.301How to use a DOI?
- Gesture recognition, Gaussian model, Skin segmentation, Otsu algorithm
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.
- © 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/).
Cite this article
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 -