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Region growing is a simple region-based image segmentation method. It is also classified as a pixel-based image segmentation method since it involves the selection of initial seed points . This approach to segmentation examines neighboring pixels of initial seed points and determines whether the pixel neighbors should be added to the region.
This process continues until all pixels are assigned to a region. Because seeded region growing requires seeds as additional input, the segmentation results are dependent on the choice of seeds, and noise in the image can cause the seeds to be poorly placed. Another region-growing method is the unseeded region growing method. It is a modified ...
Statistical region merging (SRM) is an algorithm used for image segmentation. [ 1 ] [ 2 ] The algorithm is used to evaluate the values within a regional span and grouped together based on the merging criteria, resulting in a smaller list.
The lambda-connected segmentation is a region-growing segmentation method in general. It can also be made for split-and-merge segmentation. [ 4 ] Its time complexity also reaches the optimum at O ( n l o g n ) {\displaystyle O(nlogn)} where n {\displaystyle n} is the number of pixels in the image.
Range segmentation is the task of segmenting (dividing) a range image, an image containing depth information for each pixel, into segments (regions), so that all the points of the same surface belong to the same region, there is no overlap between different regions and the union of these regions generates the entire image.
Region growing segmentation - merge the points that are close enough in terms of the smoothness constraint; Color-based region growing segmentation - same concept as the Region growing, but uses color instead of normals; Min-Cut based binary segmentation - divides the cloud on foreground and background sets of points
Region growing; Rigid motion segmentation; S. Scale-space segmentation; Segmentation-based object categorization; Simple interactive object extraction;
Split and merge segmentation is an image processing technique used to segment an image. The image is successively split into quadrants based on a homogeneity criterion and similar regions are merged to create the segmented result.