Computing the component-labeling and the adjacency tree of a binary digital image in near logarithmic-time

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Abstract

Connected component labeling (CCL) of binary images is one of the fundamental operations in real time applications. The adjacency tree (AdjT) of the connected components offers a region-based representation where each node represents a region which is surrounded by another region of the opposite color. In this paper, a fully parallel algorithm for computing the CCL and AdjT of a binary digital image is described and implemented, without the need of using any geometric information. The time complexity order for an image of m× n pixels under the assumption that a processing element exists for each pixel is near O(log(m+ n) ). Results for a multicore processor show a very good scalability until the so-called memory bandwidth bottleneck is reached. The inherent parallelism of our approach points to the direction that even better results will be obtained in other less classical computing architectures.

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Díaz del Río, F., Molina-Abril, H., & Real, P. (2019). Computing the component-labeling and the adjacency tree of a binary digital image in near logarithmic-time. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11382 LNCS, pp. 82–95). Springer Verlag. https://doi.org/10.1007/978-3-030-10828-1_7

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