Abstract
This paper presents a new approach on nipple detection for adult content recognition, it combines the advantage of Adaboost algorithm that is rapid speed in object detection and the robustness of nipple features for adaptive nipple detection. This method first locates the potential nipple-like region by using Adaboost algorithm for fast processing speed. It is followed by a nipple detection using the information of shape and skin color relation between nipple and non-nipple region. As this method uses the nipple features to conduct the adult image detection, it can achieve more precise detection and avoids other methods that only detect the percentage of exposure skin area to decide whether it is an adult image. The proposed method can be also used for other organ level detection. The experiments show that our method performs well for nipple detection in adult images.
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Wang, Y., Li, J., Wang, H., Hou, Z. (2010). Automatic Nipple Detection Using Shape and Statistical Skin Color Information. In: Boll, S., Tian, Q., Zhang, L., Zhang, Z., Chen, YP.P. (eds) Advances in Multimedia Modeling. MMM 2010. Lecture Notes in Computer Science, vol 5916. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11301-7_63
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DOI: https://doi.org/10.1007/978-3-642-11301-7_63
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-11300-0
Online ISBN: 978-3-642-11301-7
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