Timeline for Image transformation to break up connected components
Current License: CC BY-SA 3.0
8 events
| when toggle format | what | by | license | comment | |
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| Oct 10, 2015 at 17:58 | vote | accept | arax | ||
| Oct 10, 2015 at 15:22 | comment | added | Stephen Luttrell |
Here's a solution: ImageCorrelate[image, GaussianMatrix[3]] // MaxDetect // ComponentMeasurements[#, "Centroid"][[All, 2]] & // VoronoiMesh // HighlightMesh[#, {Style[1, Red], Style[2, Opacity[0]]}] & // Show[image, #] &. The sequence of operations, reading left to right along the processing pipeline, is smooth to reduce noise, detect peaks, find centroids of peaks, convert to Voronoi mesh, highlight the mesh itself but make its cells invisible, overlay the mesh on the original image.
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| Oct 10, 2015 at 15:17 | answer | added | bill s | timeline score: 4 | |
| Oct 10, 2015 at 14:33 | answer | added | Niki Estner | timeline score: 8 | |
| Oct 10, 2015 at 12:39 | comment | added | arax |
@Pickett Thanks for the information, I think the main problem is that I can't find a proper threshold for Binarize to break apart the joining spheres without losing some darker ones on the left.
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| Oct 10, 2015 at 11:25 | comment | added | C. E.♦ |
Sorry, I accidentally removed my comment because it didn't show me your comment and I wanted to add something to mine. This is the post I linked to. It can find the maximums, even if WatershedComponents doesn't work. This should be enough to generate the Voronoi diagram, is this enough for you?
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| Oct 10, 2015 at 11:23 | comment | added | arax |
@Pickett Yeah I found that post and played with some parameters there, WatershedComponents tend to partition the background into multiple components probably because this image is packed. And still I can't find a proper threshold for Binarize to break up the spheres without losing some darker ones on the left.
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| Oct 10, 2015 at 10:29 | history | asked | arax | CC BY-SA 3.0 |