This forum is disabled, please visit https://forum.opencv.org
| 2018-07-28 03:45:33 -0600 | received badge | ● Enthusiast |
| 2018-07-24 06:39:17 -0600 | received badge | ● Supporter (source) |
| 2018-07-23 09:11:59 -0600 | commented answer | Separate HSV mask I review some topic about the Sobel filter. It seem that it use for edge detection. So, how to apply for defining edge d |
| 2018-07-23 09:07:16 -0600 | marked best answer | Separate HSV mask The following is the original image :
Then, I used the HSV inrange to filter the guidepath. And then the result like this:
Is there has any method so that I can separte the guidepath into 3 direction? Just similar the following:
Updated The following image has already completed the first 2 (@StevenPuttemans suggestion) step
I also use 100*100 sliding window to scan thought the whole image. And then calculating the mean point inside the sliding window. The result like following:
|
| 2018-07-23 09:07:16 -0600 | received badge | ● Scholar (source) |
| 2018-07-23 08:10:20 -0600 | commented answer | Separate HSV mask The first 2 step I implemented yesterday. But I have no knowledge about gradients of the image. Could you introduce some |
| 2018-07-23 08:08:31 -0600 | received badge | ● Editor (source) |
| 2018-07-23 08:08:31 -0600 | edited question | Separate HSV mask Separate HSV mask The following is the original image : Then, I used the HSV inrange to filter the guidepath. And the |
| 2018-07-21 00:33:10 -0600 | asked a question | Separate HSV mask Separate HSV mask The following is the original image : Then, I used the HSV inrange to filter the guidepath. And the |
Then, I use the minmum spanning tree with euclidean distance to create the relationship between these point. Now, I have no idea how to remove noise edge in tree and confirm different direction. Anyone have a good suggestion?