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http://dx.doi.org/10.9728/dcs.2017.18.8.1603

Noise-robust Hand Region Segmentation In RGB Color-based Real-time Image  

Yang, Hyuk Jin (Dept. of Computer Science, Gyeongsang Nat'l University)
Kim, Dong Hyun (Dept. of Computer Science and CCBM, Graduate School, Gyeongsang Nat'l University)
Seo, Yeong Geon (Dept. of Computer Science and CCBM, Graduate School, Gyeongsang Nat'l University)
Publication Information
Journal of Digital Contents Society / v.18, no.8, 2017 , pp. 1603-1613 More about this Journal
Abstract
This paper proposes a method for effectively segmenting the hand region using a widely popular RGB color-based webcam. This performs the empirical preprocessing method four times to remove the noise. First, we use Gaussian smoothing to remove the overall image noise. Next, the RGB image is converted into the HSV and the YCbCr color model, and global fixed binarization is performed based on the statistical value for each color model, and the noise is removed by the bitwise-OR operation. Then, RDP and flood fill algorithms are used to perform contour approximation and inner area fill operations to remove noise. Finally, ROI (hand region) is selected by eliminating noise through morphological operation and determining a threshold value proportional to the image size. This study focuses on the noise reduction and can be used as a base technology of gesture recognition application.
Keywords
RGB Color; Hand Region; Hand Region Segmentation; Gausian Smoothing; Flood Fill;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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