@inbook{465811ce733b42d09ef22600020baefb,
title = "Pixel Classification for Skin Detection in Color Images",
abstract = "In this paper a direct, pixel-based skin detection method is proposed and evaluated. Proposed approach discards any spatial information that can be found in digital image and focuses entirely on data-oriented analysis. To ensure the best perfomance two classifiers (Regularized Logistic Regression and Artificial Neural Network with Regularization trained with Backpropagation) were deeply examined, evaluated and compared for this task. The best model achieved the almost perfect accuracy and quality of classification on the used {\textquoteleft}Skin Segmentation Dataset{\textquoteright} provided for the UCI Machine Learning Repository with over 99\% accuracy, precision, recall and specificity.",
keywords = "Classification, Color image, Logistic regression, Machine learning, Neural networks, Skin detection",
author = "Bartosz Binias and Mariusz Fr{\c a}ckiewicz and Krzysztof Jaskot and Henryk Palus",
note = "Publisher Copyright: {\textcopyright} 2018, Springer International Publishing AG.",
year = "2018",
doi = "10.1007/978-3-319-64674-9\_6",
language = "English",
series = "Studies in Systems, Decision and Control",
publisher = "Springer International Publishing",
pages = "87--99",
booktitle = "Studies in Systems, Decision and Control",
address = "Switzerland",
}