Image Segmentation - Split-and-merge Methods

Split-and-merge Methods

Split-and-merge segmentation is based on a quadtree partition of an image. It is sometimes called quadtree segmentation.

This method starts at the root of the tree that represents the whole image. If it is found non-uniform (not homogeneous), then it is split into four son-squares (the splitting process), and so on so forth. Conversely, if four son-squares are homogeneous, they can be merged as several connected components (the merging process). The node in the tree is a segmented node. This process continues recursively until no further splits or merges are possible. When a special data structure is involved in the implementation of the algorithm of the method, its time complexity can reach, an optimal algorithm of the method.

Read more about this topic:  Image Segmentation

Famous quotes containing the word methods:

    We are lonesome animals. We spend all our life trying to be less lonesome. One of our ancient methods is to tell a story begging the listener to say—and to feel—”Yes, that’s the way it is, or at least that’s the way I feel it. You’re not as alone as you thought.”
    John Steinbeck (1902–1968)