HSV color space

The transformation from RGB color space to HSV color space is given by 

The HSV as well as the HSI coordinate system has several drawbacks (Hanbury and Serra 2003). Colors with a low intensity may be described as being fully saturated. For instance, the color [0.01, 0, 0] has a saturation of 1 even though for all practical purposes it is indistinguishable from black, which has a saturation of zero. Thus, dark regions of an image usually have a noisy saturation. 

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Figure 5.7 HSV color space. The RGB cube is projected along onto a plane that is perpendicular to the gray vector. The result is a hexagonal disk.

Figure 5.9 Saturation and hue of a color c as defined in the HSV color space.

A common way of color analysis is available by the use of the HS V color space. For this, a color is given by the hue (H), the saturation (S), and the value of the brightness (V). The hue value can be interpreted as an angle in the HSV color space. The corresponding colors vary from red through yellow, green, cyan, blue, magenta, and back to red. The RGB information can be converted into hue with a certain formula in such a way that the color information is available in the form of a scalar ... 

Preprocessing for texture, shape and quality characteristic features extraction convert the image to grayscale if needed and resize the image to 100x100 pixels. As for color feature the RGB image need to convert to HSV color space. 

The HSV (Hue, Saturation, Value) model, also known as HSB (Hue, Saturation, Brightness), defines a color space in terms of three constituent components ... 

The HSV model was created in 1978 by Alvy Ray Smith. It is a nonlinear transformation of the RGB color space and may be used in color progressions. 

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