Why Do We Convert From RGB To HSV - Opencv - Stack Overflow

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Learn more about Labs Why do we convert from RGB to HSV Ask Question Asked 11 years, 5 months ago Modified 7 years, 5 months ago Viewed 35k times 17

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

• opencv
• image-processing

Share Improve this question Follow edited Jun 12, 2013 at 10:30 kerry_13 asked Jun 12, 2013 at 10:20 kerry_13kerry_13 28911 gold badge33 silver badges1212 bronze badges Add a comment |

4 Answers 4

Sorted by: Reset to default Highest score (default) Trending (recent votes count more) Date modified (newest first) Date created (oldest first) 17

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.

Share Improve this answer Follow answered Jun 12, 2013 at 10:34 GPPKGPPK 6,64655 gold badges3535 silver badges5959 bronze badges Add a comment | 10

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

Share Improve this answer Follow answered Jun 12, 2013 at 10:31 IntermernetIntermernet 19.3k44 gold badges5050 silver badges6161 bronze badges Add a comment | 5

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.

Share Improve this answer Follow answered Jun 12, 2013 at 10:35 Boyko PerfanovBoyko Perfanov 3,0472020 silver badges3535 bronze badges Add a comment | 3

R, G, B in RGB are all co-related to the color luminance( what we loosely call intensity),i.e., We cannot separate color information from luminance. HSV or Hue Saturation Value is used to separate image luminance from color information. This makes it easier when we are working on or need luminance of the image/frame. HSV also used in situations where color description plays an integral role.

Cheers

Share Improve this answer Follow answered Jun 19, 2017 at 6:59 0AJ00AJ0 8811 gold badge33 silver badges1010 bronze badges Add a comment |

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