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A Comprehensive Investigation of Color Models used in Image Processing

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2018
Kondekar Vipul H., Bodhe S. K.

Kondekar Vipul H. and Bodhe S K.. A Comprehensive Investigation of Color Models used in Image Processing. International Journal of Computer Applications 180(22):19-24, February 2018. BibTeX

	author = {Kondekar Vipul H. and Bodhe S. K.},
	title = {A Comprehensive Investigation of Color Models used in Image Processing},
	journal = {International Journal of Computer Applications},
	issue_date = {February 2018},
	volume = {180},
	number = {22},
	month = {Feb},
	year = {2018},
	issn = {0975-8887},
	pages = {19-24},
	numpages = {6},
	url = {},
	doi = {10.5120/ijca2018916507},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


This paper is a study of different color models for color image processing. Color has been recognized as an important visual aspect for image and scene analysis. Research work in color image processing has focused on color image formation, color quantization, human visual perception, image segmentation, color-based object recognition, and image database retrieval. RGB color space is generally adopted by image acquisition device, while other kinds of color space are derived from RGB space by using either linear or nonlinear transformations. The choice of a color space is important for many computer image processing algorithms (e.g., feature detection, image classification, object recognition, and visual tracking). No color space can be considered as universal because color can be interpreted and modeled in different ways. With the large variety of available color spaces the inevitable question that arises is how to select the color model that produces the best result for a particular computer vision task. In this paper, the main aim is to survey the theory of different color spaces since the performance of an image analysis procedure is known to depend on the choice of the color space.


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RGB, HSV, CMYK, YCbCr , CIE; Space transformation.