원문정보
초록
영어
Aiming at the problems that current skin-color detection segmentation technologies have unsatisfied segmentation results under conditions of complex illumination or backgrounds, we present a new method based on YCbCr color space and K-means clustering algorithm for segmentation hand gesture. Firstly, image in RGB color space is converted to YCbCr color space; and then YCbCr color space of image is divided into luminance Y and chrominance Cb and Cr. Lastly, the binary image is achieved by clustering values of chrominance using k-means clustering algorithm, and hand gesture segmentation is completed by conducting morphological process of binary image obtained. The experimental results illustrate that the proposed method can segment hand gestures from complex backgrounds and obtain segmentation results. The phenomena of similar skin color interference and skin color overlapping are solved with this method effectively. In addition, it is robust to illumination condition.
목차
1. Introduction
2. Color Spaces
2.1. RGB Color Space
2.2. HSV Color Space
2.3. YCbCr Color Space
2.4. Color Spaces Analysis and Selection
3. Hand Gesture Segmentation Method Based on YCbCr Color Space and K-means Clustering
3.1. Hand Segmentation Processing Procedure
3.2. Color Space Means Clustering
3.3. K-means Clustering of Chromaticity Value
3.4 Morphology Process
4. Experiment Results and Analysis
5. Conclusions
Acknowledgments
References