CODEWITHSUNDEEP
image-processingimage-segmentation
Premnath D
Premnath D

Reputation: 249

Region growing Vs Clustering

In image processing, how region growing and clustering differ from each other ? Give more information on how they differ. Thank you for reading

Upvotes: 3

Views: 2366

Answers (2)

R H
R H

Reputation: 1

I found region growing similar to some clustering algorithm. I explained my view point below:

In region growing there are 2 cases:

  1. Selecting seed points randomly which is similar to k-mean. seeds play the role of means here. Then, we start with one seed and spread it until we cannot grow it anymore (like we start with one mean and we continue till we reach a convergence). and the way we grow the region is based on the euclidean distance form seed grey value (usually).
  2. Second case in region growing can be considered with no seed (assume we don't know how many seeds to choose or we don't know the number of clusters). So we start with the first pixel. Then we find neighbors of current pixel with considering distance d from mean grey value of the region (of course at first iteration mean grey value is exactly current grey value). Afterwards, we update the mean grey value. In this way region growing seems to act like mean shift algorithm. If we don't update mean grey value after each assigning, then it could be considered as a DBSCAN algorithm.

Upvotes: 0

Olivier A
Olivier A

Reputation: 842

Region growing : You have to select seed points and then the local area around the seed is analyzed in order to know if the neighbor pixels should have the same label. http://en.wikipedia.org/wiki/Region_growing It can be used for precise image segmentation.

Clustering : There are many clustering techniques (k-means, hierarchical clustering, density clustering, etc.). Clustering algorithms don't ask to input seed points because they are based on unsupervised learning.
It can be use for coarse image segmentation.

Upvotes: 2

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