Question

I’m using the Emgu shape detection example application to detect rectangles on a given image. The dimensions of the resized image appear to impact the number of shapes detected even though the aspect ratio remains the same. Here’s what I mean:

Using (400,400), actual img size == 342,400

Using (520,520), actual img size == 445,520

Why is this so? And how can the optimal value be determined?

Thanks

Answer 1

I replied to your post on EMGU but figured you haven’t checked back but this is it. The shape detection works on the principle of thresh-holding unlikely matches, this prevents lots of false classifications. This is true for many image processing algorithms. Basically there are no perfect setting and a designer must select the most appropriate settings to produce the most desirable results. I.E. match the most objects without saying there’s more than there actually is.

You will need to adjust each variable individually to see what kind of results you get. Start of with the edge detection.

Image<Gray, Byte> cannyEdges = gray.Canny(cannyThreshold, cannyThresholdLinking);

Have a look at your smaller image see what the difference is between the rectangles detected and the one that isn’t. You could be missing and edge or a corner which is why it’s not classified. If you are adjust cannyThreshold and observe the results, if good then keep it 🙂 if bad 🙁 go back to the original value. Once satisfied adjust cannyThresholdLinking and observe.

You will keep repeating this until you get a preferred image the advantage here is that you have 3 items to compare you will continue until the item that’s not being recognised matches the other two.

If they are the similar, likely as it is a black and white image you’ll need to go onto the Hough lines detection.

        LineSegment2D[] lines = cannyEdges.HoughLinesBinary(
            1, //Distance resolution in pixel-related units
            Math.PI / 45.0, //Angle resolution measured in radians.
            20, //threshold
            30, //min Line width
            10 //gap between lines
            )[0]; //Get the lines from the first channel

Use the same method of adjusting one value at a time and observing the output you will hopefully find the settings you need. Never jump in with both feet and change all the values as you will never know if your improving the accuracy or not. Finally if all else fails look at the section that inspects the Hough results for a rectangle

                      if (angle < 80 || angle > 100)
                       {
                          isRectangle = false;
                          break;
                       }

Less variables to change as hough should do all the work for you. but still it could all work out here.

I’m sorry that there is no straight forward answer, but I hope you keep at it and solve the problem. Else you could always resize the image each time.

Cheers

Chris