Kim, Chiho You, Bum-Jae Jeong, Mun-Ho Kim, Hagbae 2024-01-21T00:02:30Z 2024-01-21T00:02:30Z 2021-09-02 2008-01 0031-3203 https://pubs.kist.re.kr/handle/201004/133858 Color segmentation takes a great attention because color is an effective and robust visual cue for characterizing an object from the others. However, color segmentation suffers from color variations incurred by irregular illumination changes. We propose a reliable color modeling approach in hue-saturation-intensity (HSI) color space while considering intensity information by adopting the B-spline curve fitting to make a mathematical model for statistical characteristics of a color with respect to intensity. It is based on the fact that color distribution of a single-colored object is not invariant with respect to brightness variations even in the HS (hue-saturation) plane. The statistical characteristics contain the mean and standard deviation of hue and saturation with respect to intensity. They are mathematically expressed as four bar graphs. In order to fit the bar graphs to continuous curves, we use B-spline curve fitting procedure. From several experimental results, we verify that the proposed algorithm is successfully applied to color segmentation under various illumination conditions. (C) 2007 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved. English ELSEVIER SCI LTD FACE DETECTION SKIN Color segmentation robust to brightness variations by using B-spline curve modeling Article 10.1016/j.patcog.2007.04.011 1 PATTERN RECOGNITION, v.41, no.1, pp.22 - 37 PATTERN RECOGNITION 41 1 22 37 scie scopus 000250028700002 2-s2.0-34548030243 Computer Science, Artificial Intelligence Engineering, Electrical & Electronic Computer Science Engineering Article FACE DETECTION SKIN color consistency color segmentation B-spline curve brightness variations color model