Color segmentation robust to brightness variations by using B-spline curve modeling |
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| Authors: | Chiho Kim Bum-Jae You Mun-Ho Jeong Hagbae Kim |
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| Affiliation: | 1. Center for Cognitive Robotics, KIST, P.O. Box 131, Cheongryang, Seoul 130-650, Republic of Korea;2. Department of Electrical and Electronic Engineering, Yonsei University, 134, Shinchon-dong, Seodaemun-ku, Seoul 120-749, Republic of Korea;1. Department of Mechanical Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel;2. Global General Motors R&D, Manufacturing Systems Research Lab, Warren, MI 48090, USA;1. Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an 710049, China;2. Department of Dermatology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710049, China;1. Institute for Pattern Recognition & Artificial Intelligence, School of Automation, Huazhong University of Sci. & Tech., Wuhan 430074, China;2. Meteorological Observation Centre of China Meteorological Administration, Beijing 100081, China;1. Department of Kinesiology, University of Wisconsin, Milwaukee, WI 53201, USA;2. Department of Biomedical Engineering, Marquette University, Milwaukee, WI 53233, USA;3. Department of Physical Medicine and Rehabilitation, Medical College of Wisconsin, Milwaukee, WI 53226, USA;1. Department of Radiology, ?ifa University School of Medicine, ?zmir, Turkey;2. Department of Obstetrics and Gynecology, ?ifa University School of Medicine, ?zmir, Turkey;3. Department of Radiology, Atatürk University School of Medicine, Erzurum, Turkey;4. Department of Pathology, ?ifa University School of Medicine, ?zmir, Turkey |
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| Abstract: | 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. |
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