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.
Every picture tells a story, by colors.
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Zhang, D. (2019). Color Feature Extraction. In: Fundamentals of Image Data Mining. Texts in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-030-17989-2_4
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DOI: https://doi.org/10.1007/978-3-030-17989-2_4
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