i want to detect red objects in an image.so i convert RGB img to HSV. so in order to know the range of red color i used color pallet on this site
https://alloyui.com/examples/color-picker/hsv
I found out that H(Hue) is falling between 0 to 10 as a lower limit and 340 to 359 as an upper limit. also i found out that the maximum value of S(Saturation) and V(value) is 100. but the problem is that i found some people say the ranges of red H: 0 to 10 as lower limit and 160 to 180 as uper limit.
https://solarianprogrammer.com/2015/05/08/detect-red-circles-image-using-opencv/
OpenCV better detection of red color?
also they said the maximum S and V is 255.This is color i got when i tried to find the upper limit of the red
Whats the ranges of the red in HSV
hsvimage processing
Related Solutions
An alternative approach would be to extract features (keypoints) using the scale-invariant feature transform (SIFT) or Speeded Up Robust Features (SURF).
You can find a nice OpenCV code example in Java, C++, and Python on this page: Features2D + Homography to find a known object
Both algorithms are invariant to scaling and rotation. Since they work with features, you can also handle occlusion (as long as enough keypoints are visible).
Image source: tutorial example
The processing takes a few hundred ms for SIFT, SURF is bit faster, but it not suitable for real-time applications. ORB uses FAST which is weaker regarding rotation invariance.
The original papers
This is kind of late, but this is what I'd try.
Make the conversion: cvCvtColor(imageBgr, imageHsv, CV_RGB2HSV);
Note, RGB vs Bgr are purposefully being crossed.
This way, red color will be treated in a blue channel and will be centered around 170. There would also be a flip in direction, but that is OK as long as you know to expect it.
Best Answer
There are different definitions of HSV, so the values your particular conversion function gives are the ones your should use. Measuring them is the best way to know for sure.
In principle H is an angle, so it goes from 0 to 360, with red centered around 0 (and understanding that 360==0). But some implementations will divide that by 2 to fit it in 8 bits. Others scale to a full 0-255 rage for the 8 bits.
The same is true for S and V. Sometimes they're values between 0 and 100, sometimes they go up to 255.
To measure, create an image where you have pure red pixels (RGB value 255,0,0), and convert. That will give your the center of red hue (H) and the max saturation (S). Then make an image that changes from orange to purple, these colors are near red. You should then see the range of H. Finally, make a pure white image (255,255,255). This will have maximum intensity (V).