Compute edge for intensity decreases only

1
votes

I want to find edges in my image, specifically vertical changes in intensity which go from light to dark. Is this possible? I'm using the Canny/Sobel edge detectors in OpenCV but they're picking up edges where the intensity increases, which I don't want.

2
c++opencvimage-processingcomputer-visionedge-detection
you can try sobel filter in x-direction: Sobel( src_gray, grad_x, ddepth, 1, 0, 3, scale, delta, BORDER_DEFAULT ); from docs.opencv.org/doc/tutorials/imgproc/imgtrans/… – Micka
If you could include a minimal working example that would be great. And maybe you could include one example image that shows what goes on. – Unapiedra

2 Answers

0
votes

You can write a custom filter and use cvFilter2D (2D convolution).

To give a very simple example, the convolution kernel {1 0 -1;1 0 -1; 1 0 -1} is a 3x3 filter that can highlight intensity decreases going from left to right. You can threshold the result to get the edges.

You will have to select the right size of the kernel, and also the right values, to suit your images.

Here is a good link that shows how to use cvFilter2d:

0
votes

Once you understand what these filters do mathematically, it is quite clear what and you have to change. And where in the pipeline this must be. In his answer, Totoro already pointed out that you can pass your own filters to be run.

Sobel edge detection works by first running two filters on the image. These filters give the gradient of the image in X and Y direction. Edges and gradients are linked in the way that a large magnitude of the gradient means that there is a lot of change in the image, which would indicate an edge!

So the next step (iirc) in the Sobel algorithm is to find the magnitude of the gradients. And finally you threshold this, to take only large changes in the image as edges. Finally, you do some edge thinning and hysteresis thresholding along the direction of the edge but that is not very important here.

The important step where you want to be different than the Sobel algorithm is that you care about the direcction of change. If you compute the direction of change from the X and Y gradients (using sine and cosine), then you can filter out edges that only go in the direction you want.

If you just care about vertical changes, you can run a convolution kernel that computes the gradient along the horizontal and take only positive values. All positive values will indicate that there was a vertical change from light to dark. If you want you can do the following processing steps just as Sobel would do.