How can edge detection be used for image segmentation?

How can edge detection be used for image segmentation?

Edge detection techniques are generally used for finding discontinuities in gray level images. To detect consequential discontinuities in the gray level image is the important common approach in edge detection. Image segmentation methods for detecting discontinuities are boundary based methods.

What is canny edge detection in image processing?

The Canny edge detector is an edge detection operator that uses a multi-stage algorithm to detect a wide range of edges in images. It was developed by John F. Canny in 1986. Canny also produced a computational theory of edge detection explaining why the technique works. (

What’s the difference between Canny edge detection and contour detection?

As can be read in the documentation, detecting contours is mostly used for object recognition, whereas the canny edge detector is a more “global” operation. I wouldn’t be surprised if the contour algorithm uses some sort of canny edge detection. The notion of contours is used as a tool to work on edge data. Not all edges are the same.

How to improve contour detection in Python stack?

Dilate and erode the binary masks to bridge any one or two pixels gaps between contour fragments. Use maximal supression to turn your thick binary masks along the boundary of your shapes into thin edges. As used earlier in the pipeline, use cvFindcontours to identify closed contours.

How can I improve my image segmentation results?

Might have improved results a bit, e.g., in the bad example above the first column third row card is now correctly segmented. Using histogram equalization to enhance contrast. Generally obscured some necessary edges.

How are edge pixels different from image contours?

The point is, edge pixels are a local notion: they just point out a significant difference between neighbouring pixels. Contours are often obtained from edges, but they are aimed at being object contours. Thus, they need to be closed curves. You can think of them as boundaries (some Image Processing algorithms & librarires call them like that).