Connected component labeling is a fundamental task in computer vision. This paper presents parallel implementations of connected component labeling for grey level images on the iPSC/2 and iPSC \(/ 860\) hypercubes, the CM-5, and on the shared memory Encore Multimax multiprocessor. Several partitioni
Algorithms for connected component labeling based on quadtrees
β Scribed by Kunio Aizawa; Shojiro Tanaka; Koyo Motomura; Ryosuke Kadowaki
- Publisher
- John Wiley and Sons
- Year
- 2009
- Tongue
- English
- Weight
- 346 KB
- Volume
- 19
- Category
- Article
- ISSN
- 0899-9457
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β¦ Synopsis
Abstract
An algorithm of linear time complexity is presented to label connected components of a binary image by a quadtree. For a given node, the search for all adjacent nodes is carried out in O(1) (i.e., constant time complexity for the worst case) using our formerly presented algorithm in (Aizawa et al., 3rd International Symposium on Communications, Control, and Signal Processing,2008, 505β510), whereas it explores all possible adjacencies for each node in a usual way. Then during the process of tree formulation in the search, all equivalent relations of labels are stored as lists. Time complexity of the algorithm is O(B+W) for the worst case and its auxiliary space is no more than O(B), where B and W correspond to the number of leaf nodes in a quadtree representing black and white quadrants, respectively. Empirical tests of the algorithm are employed in comparison with another linear time connected component labeling algorithm based on topβdown quadtree traversal algorithm (Samet, IEEE Trans Pattern Anal Mach Intell PAMIβ7 (1985), 94β98), as well as traditional rowβbyβrow scanning algorithm using linear time UnionβFind (Fiorio and Gustedt, Theor Comput Sci 154 (1996), 165β181). Our algorithm has shown the best performance in large images. Β© 2009 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 19, 158β166, 2009.
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