A Robust Detection Method of Body Areas Using Adaboost

摘要

The present invention relates to a robust detection method of a human body region using Adaboost for robustly detecting a navel region, which can be usefully used for detecting a harmful image by analyzing an input image, comprising the steps: (a) extracting a skin region from an input image using a skin color distribution; (b) extracting at least two nipple regions using a nipple map in the skin region; (c) separately processing an edge and a chroma of the input image to obtain an edge image and a chroma image, and extracting a region located within the nipple regions and a predetermined geometric range from overlapping regions in the edge image and the chroma image as a navel candidate region; and (d) extracting a Harr-like feature from the navel candidate region, applying the Harr-like feature to an Adaboost classifier, and determining whether the navel candidate region is a navel region in accordance with a result of the Adaboost classifier to extract the same. Accordingly, a navel region can be more accurately extracted from an input color image compared to a conventional method by robustly detecting the navel region using the Harr-like feature and an Adaboost method.