Getting Hue value from the peaks in histogram opencv

1
votes

I am trying to use color information of detection of rectangles. Some of my rectangles are overlapping and with multicolor. I found a solution to detect these rectangles using Hue values. I am checking inRange with Hue values of colors

  • Orange 0-22
  • Yellow 22- 38
  • Green 38-75
  • Blue 75-130
  • Violet 130-160
  • Red 160-179

, but I do not know what exact color is going to be. For example, in one image rectangles can be orange, red, blue and in another image, it can be other colors.

I tried to look histogram, but I would have a background which is not only white or black. So, the histogram is confusing.

If you give me some ideas about how to handle this problem, I will appreciate it.

2
c++opencvimage-processinghistogram
may be post some example images. what portion of the screen the rectangles take? can you remove them with some morphological filters. is the background structured or single colored? – vlad_tepesch
Please post representative images. – Mark Setchell

2 Answers

1
votes

You can try a brute force approach, where you try all the color ranges, then use findcontours (example) to see if you can find a contour that is possibly a rectangle. If the background is very noisy you can use a minimum size for the contour (contourArea). You could also check the solidity by dividing the contour area by the area of the minAreaRect, the result for a rectangle (that has good detection) should approach 1.

Whether this could possibly work depends on several factors, and overlapping rectangles will quickly break it.

0
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So if I understand correctly, you have a variety of images, each of which contain multiple rectangles which can be a variety of different colors, and the background of the image is non uniform, and you're trying to segment out the rectangles using a histogram?

Using histograms for image segmentation works best with grey scale images with a uniform background, so that upon seeing the peeks in your histogram you know the primary intensities of the objects you are trying to segment out. This method is not going to translate well to your application because the shapes you are attempting to segment are non uniform in shade, without seeing example images I would probably say this isn't going to work, however you might be able to get away with it if the shade variation of the rectangles is relatively similar... basically if you have rectangles that are 15-30 you might be alright, but if they vary from 20-100 you're going to be out of luck, same goes with variation of the background.

If the background and the rectangles have very clearly defined borders, and the background colors transition VERY smoothly, you may be able to get away with some sort of region growing on the background in order to get a list of all the background pixels and then just set those to black or something in order to allow better analysis of the rectangles in the foreground, but I can only speculate so much with the information you've given in your post