4 April 1997 Color segmentation in the HSI color space using the K-means algorithm
Author Affiliations +
Segmentation of images is an important aspect of image recognition. While grayscale image segmentation has become quite a mature field, much less work has been done with regard to color image segmentation. Until recently, this was predominantly due to the lack of available computing power and color display hardware that is required to manipulate true color images (24-bit). TOday, it is not uncommon to find a standard desktop computer system with a true-color 24-bit display, at least 8 million bytes of memory, and 2 gigabytes of hard disk storage. Segmentation of color images is not as simple as segmenting each of the three RGB color components separately. The difficulty of using the RGB color space is that it doesn't closely model the psychological understanding of color. A better color model, which closely follows that of human visual perception is the hue, saturation, intensity model. This color model separates the color components in terms of chromatic and achromatic information. Strickland et al. was able to show the importance of color in the extraction of edge features form an image. His method enhances the edges that are detectable in the luminance image with information from the saturation image. Segmentation of both the saturation and intensity components is easily accomplished with any gray scale segmentation algorithm, since these spaces are linear. The modulus 2(pi) nature of the hue color component makes its segmentation difficult. For example, a hue of 0 and 2(pi) yields the same color tint. Instead of applying separate image segmentation to each of the hue, saturation, and intensity components, a better method is to segment the chromatic component separately from the intensity component because of the importance that the chromatic information plays in the segmentation of color images. This paper presents a method of using the gray scale K-means algorithm to segment 24-bit color images. Additionally, this paper will show the importance the hue component plays in the segmentation of color images.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Arthur Robert Weeks, Arthur Robert Weeks, G. Eric Hague, G. Eric Hague, "Color segmentation in the HSI color space using the K-means algorithm", Proc. SPIE 3026, Nonlinear Image Processing VIII, (4 April 1997); doi: 10.1117/12.271117; https://doi.org/10.1117/12.271117


Efficient graph-cut tattoo segmentation
Proceedings of SPIE (March 03 2015)
Color document analysis
Proceedings of SPIE (December 27 2001)
Color image modeling based on edge detection
Proceedings of SPIE (October 09 1994)
Study of robot landmark recognition with complex background
Proceedings of SPIE (January 08 2008)
Human visual-system-based image enhancement
Proceedings of SPIE (May 01 2007)

Back to Top