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Wavelet-Based Morphological Approach for Detection of Human Face Region
Quebec City, QC, Canada August 11-August 15
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2002.104474116th International Conference on Patt ...
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Jong Bae Kim, Kyungpook National University
Chae Hyun Moon, Kyungpook National University
Hang Joon Kim, Kyungpook National University
In this paper, we present a novel method to detect a human skin region from a given head and shoulder image. The presented method consists of two stages: region segmentation and facial region detection. In the region segmentation, the input image is segmented into an appropriate set of arbitrary regions using the wavelet-based watershed algorithm. Then, to merge the regions forming an object, we use a spatial similarity between two regions since the regions forming an object share some common wavelet characteristics. In facial region detection, the facial regions are identified from the segmented results using a skin-color model. The results of region segmentation and facial region detection are integrated to provide facial regions with accurate and closed boundaries. In our experiments, the algorithm detected 87-94% of the faces, including frames from videoconference sequences. The average run time range from 0.23-0.34 sec per frame.
Citation:
Jong Bae Kim, Chae Hyun Moon, Hang Joon Kim, "Wavelet-Based Morphological Approach for Detection of Human Face Region," icpr, vol. 1, pp.10417, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 1, 2002
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