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http://dx.doi.org/10.5762/KAIS.2016.17.11.403

Robust Detection of Body Areas Using an Adaboost Algorithm  

Jang, Seok-Woo (Department of Digital Media, Anyang University)
Byun, Siwoo (Department of Digital Media, Anyang University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.17, no.11, 2016 , pp. 403-409 More about this Journal
Abstract
Recently, harmful content (such as images and photos of nudes) has been widely distributed. Therefore, there have been various studies to detect and filter out such harmful image content. In this paper, we propose a new method using Haar-like features and an AdaBoost algorithm for robustly extracting navel areas in a color image. The suggested algorithm first detects the human nipples through color information, and obtains candidate navel areas with positional information from the extracted nipple areas. The method then selects real navel regions based on filtering using Haar-like features and an AdaBoost algorithm. Experimental results show that the suggested algorithm detects navel areas in color images 1.6 percent more robustly than an existing method. We expect that the suggested navel detection algorithm will be usefully utilized in many application areas related to 2D or 3D harmful content detection and filtering.
Keywords
Adaboost algorithm; Learning; Feature extraction; Detection accuracy; Binarization;
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