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2019 | OriginalPaper | Chapter

4. Color Feature Extraction

Author : Dr. Dengsheng Zhang

Published in: Fundamentals of Image Data Mining

Publisher: Springer International Publishing

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Abstract

This chapter focuses on one of the three major types of image features; colors. It first gives a brief introduction to color science, followed by the introduction of four color spaces commonly used in image feature extraction. Readers are demonstrated with pros and cons of each color space. Two segmentation techniques are also shown to divide an image into regions. In the next, different types of histogram features are introduced to give readers ideas on how simple features can be extracted from a color image. Finally, a number of most commonly used color features are described and discussed in details including four color descriptors standardised by MPEG-7 such as CSD, DCD, CLD, and SCD. This chapter is also a shortcut to color science, which is a complex theory.

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Literature
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8.
go back to reference Islam M, Zhang D, Lu G (2008) Automatic categorization of image regions using dominant color based vector quantization. In: Proceedings of digital image computing: techniques and applications (DICTA 2008), pp 191–198 Islam M, Zhang D, Lu G (2008) Automatic categorization of image regions using dominant color based vector quantization. In: Proceedings of digital image computing: techniques and applications (DICTA 2008), pp 191–198
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go back to reference Liu Y, Zhang D, Lu G, Ma WY (2005) Region-based image retrieval with high-level semantic color names. In: Proceedings of multimedia modelling conference, pp 180–187 Liu Y, Zhang D, Lu G, Ma WY (2005) Region-based image retrieval with high-level semantic color names. In: Proceedings of multimedia modelling conference, pp 180–187
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Metadata
Title
Color Feature Extraction
Author
Dr. Dengsheng Zhang
Copyright Year
2019
DOI
https://doi.org/10.1007/978-3-030-17989-2_4

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