Why do we convert from RGB to HSV

Question

I have a image and i want to detect a blue rectange in it. My teacher told me that:

• convert it to HSV color model
• define a thresh hold to make it become a binary image with the color we want to detect

So why do we do that ? why don't we direct thresh hold the rgb image ? thanks for answer

Answer 1

You can find the answer to your question here

the basic summary is that HSV is better for object detection,

OpenCV usually captures images and videos in 8-bit, unsigned integer, BGR format. In other words, captured images can be considered as 3 matrices, BLUE,RED and GREEN with integer values ranges from 0 to 255.

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. So, in the above application, I have converted the color space of original image of the video from BGR to HSV image.

HSV color space is consists of 3 matrices, 'hue', 'saturation' and 'value'. In OpenCV, value range for 'hue', 'saturation' and 'value' are respectively 0-179, 0-255 and 0-255. 'Hue' represents the color, 'saturation' represents the amount to which that respective color is mixed with white and 'value' represents the amount to which that respective color is mixed with black.

Answer 2

According to http://en.wikipedia.org/wiki/HSL_and_HSV#Use_in_image_analysis :

Because the R, G, and B components of an object’s color in a digital image are all correlated with the amount of light hitting the object, and therefore with each other, image descriptions in terms of those components make object discrimination difficult. Descriptions in terms of hue/lightness/chroma or hue/lightness/saturation are often more relevant.

Also some good info here