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Authors: Rodrigo Augusto Dias Faria and Roberto Hirata Jr.

Affiliation: Institute of Mathematics and Statistics and University of São Paulo, Brazil

ISBN: 978-989-758-290-5

Keyword(s): Skin Detection, Human Skin Segmentation, YCbCr Color Model, Correlation Rules, Dynamic Color Clustering.

Abstract: Skin detection plays an important role in a wide range of image processing and computer vision applications. In short, there are three major approaches for skin detection: rule-based, machine learning and hybrid. They differ in terms of accuracy and computational efficiency. Generally, machine learning and hybrid approaches outperform the rule-based methods, but require a large and representative training dataset as well as costly classification time, which can be a deal breaker for real time applications. In this paper, we propose an improvement of a novel method on rule-based skin detection that works in the YCbCr color space. Our motivation is based on the hypothesis that: (1) the original rule can be reversed and, (2) human skin pixels do not appear isolated, i.e. neighborhood operations are taken in consideration. The method is a combination of some correlation rules based on these hypothesis. Such rules evaluate the combinations of chrominance Cb, Cr values to identify the skin pixels depending on the shape and size of dynamically generated skin color clusters. The method is very efficient in terms of computational effort as well as robust in very complex image scenes. (More)

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Paper citation in several formats:
Faria, Rodrigo Augusto D. and Hirata Jr., R. (2018). Combined Correlation Rules to Detect Skin based on Dynamic Color Clustering.In Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, ISBN 978-989-758-290-5, pages 309-316. DOI: 10.5220/0006618003090316

@conference{visapp18,
author={Faria, Rodrigo Augusto D. and Roberto Hirata Jr..},
title={Combined Correlation Rules to Detect Skin based on Dynamic Color Clustering},
booktitle={Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,},
year={2018},
pages={309-316},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006618003090316},
isbn={978-989-758-290-5},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,
TI - Combined Correlation Rules to Detect Skin based on Dynamic Color Clustering
SN - 978-989-758-290-5
AU - Faria, Rodrigo Augusto D.
AU - Hirata Jr., R.
PY - 2018
SP - 309
EP - 316
DO - 10.5220/0006618003090316

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