- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
Hello,
I'm trying to implement Canny edge detector with subpixel precision. AFAIK, there is only usual (non-subpixel) detector in IPP. It accepts x and y gradient components as input and applies hysteresis thresholding based on gradient value.
The problem is, gradient value is estimated as a sum of absolute values of gradient components: mag = |dx| + |dy|. But all the rest of my algorithm (edge detection is only a small piece) uses more conventional L2 norm to estimate gradient value: mag = sqrt(dx^2 + dy^2). So inconsistencies arise in this case.
Is there a way to make Canny detector use L2 norm instead of L1, or directly pass gradient value to use?
Thanks.
I'm trying to implement Canny edge detector with subpixel precision. AFAIK, there is only usual (non-subpixel) detector in IPP. It accepts x and y gradient components as input and applies hysteresis thresholding based on gradient value.
The problem is, gradient value is estimated as a sum of absolute values of gradient components: mag = |dx| + |dy|. But all the rest of my algorithm (edge detection is only a small piece) uses more conventional L2 norm to estimate gradient value: mag = sqrt(dx^2 + dy^2). So inconsistencies arise in this case.
Is there a way to make Canny detector use L2 norm instead of L1, or directly pass gradient value to use?
Thanks.
Link Copied
0 Replies

Reply
Topic Options
- Subscribe to RSS Feed
- Mark Topic as New
- Mark Topic as Read
- Float this Topic for Current User
- Bookmark
- Subscribe
- Printer Friendly Page