Why hsv is better than rgb

So why do we do that? You can find the answer to your question here. How BGR image is formed In the above image, each small box represents a pixel of the image. In real images, these pixels are so small that human eye cannot differentiate. Usually, one can think that BGR color space is more suitable for color based segmentation. But HSV color space is the most suitable color space for color based image segmentation. HSV color space is consists of 3 matrices, 'hue', 'saturation' and 'value'.

In OpenCV, value range for 'hue', 'saturation' and 'value' are respectively , and Also some good info here. The HSV color space abstracts color hue by separating it from saturation and pseudo-illumination.

This makes it practical for real-world applications such as the one you have provided. HSV also used in situations where color description plays an integral role. Stack Overflow for Teams — Collaborate and share knowledge with a private group. Create a free Team What is Teams? With some classes benefiting from different color spaces, so not one that is best for all.

It is one of the methods I have in my toolkit and have tried it as preprocessing in two Kaggle challenges unsuccessfully, but beside the point. Thank you. Particularly if you have 4 or more channels of data eg NIR , and working out how to combine those into 3. Even on photographic images, other colorspaces often have a knack. Some say YCbCr is a better starting point for shadow detection. Experimental results have shown RGB works the best of all the standard color models. Dessert Recipes. By Thelma Alberts.

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