Abstract
This paper presents a motion-based skin Region of Interest (ROI) detection method using a real-time connected component labeling algorithm to provide real-time and adaptive skin ROI detection in video images. Skin pixel segmentation in video images is a pre-processing step for face and hand gesture recognition, and motion is a cue for detecting foreground objects. We define skin ROIs as pixels of skin-like color where motion takes place. In the skin color estimation phase, RGB color histograms are utilized to define the skin color distribution and specify the threshold to segment skin-like regions. A parallel computed connected component labeling algorithm is also proposed to group the segmentation results into several clusters. If a cluster covers any motion pixel, this cluster is identified as a skin ROI. The method’s results for real images are shown, and its speed is evaluated for various parameters. This technology is compatible with monitoring systems, scene understanding, and natural user interfaces.
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Acknowledgments
This research was supported by the MSIP(Ministry of Science, ICT and Future Planning), Korea, under the ITRC(Information Technology Research Center) support program (IITP-2015-H8501-15-1014) supervised by the IITP(Institute for Information & communications Technology Promotion), by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and future Planning (NRF-2015R1A2A2A01003779), by Science and Technology Project of Beijing Municipal Education Commission (KM2015_10009006), and by the National Natural Science Foundation of China (61503005).
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Song, W., Wu, D., Xi, Y. et al. Motion-based skin region of interest detection with a real-time connected component labeling algorithm. Multimed Tools Appl 76, 11199–11214 (2017). https://doi.org/10.1007/s11042-015-3201-5
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DOI: https://doi.org/10.1007/s11042-015-3201-5