@inproceedings{5590969ff35440b98cb18f56a500b6b8,
title = "Self-adaptive skin segmentation in color images",
abstract = "In this paper, we present a new method for skin detection and segmentation, relying on spatial analysis of skin-tone pixels. Our contribution lies in introducing self-adaptive seeds, from which the skin probability is propagated using the distance transform. The seeds are determined from a local skin color model that is learned on-line from a presented image, without requiring any additional information. This is in contrast to the existing methods that need a skin sample for the adaptation, e.g., acquired using a face detector. In our experimental study, we obtained F-score of over 0.85 for the ECU benchmark, and this is highly competitive compared with several state-of-the-art methods.",
keywords = "Adaptive skin modeling, Distance transform, Gesture recognition, Skin color, Skin detection, Skin segmentation, Spatial analysis",
author = "Michal Kawulok and Jolanta Kawulok and Jakub Nalepa and Bogdan Smolka",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2014.; 19th Iberoamerican Congress on Pattern Recognition, CIARP 2014 ; Conference date: 02-11-2014 Through 05-11-2014",
year = "2014",
doi = "10.1007/978-3-319-12568-8\_12",
language = "English",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "96--103",
editor = "Eduardo Bayro-Corrochano and Edwin Hancock",
booktitle = "Progress in Pattern Recognition Image Analysis, Computer Vision and Applications - 19th Iberoamerican Congress, CIARP 2014, Proceedings",
address = "Germany",
}