Abstract
In this paper, we present a new image segmentation algorithm which is based on local binary patterns (LBPs) and the combinatorial pyramid and which preserves structural correctness and image topology. For this purpose, we define a codification of LBPs using graph pyramids. Since the LBP code characterizes the topological category (local max, min, slope, saddle) of the gray level landscape around the center region, we use it to obtain a “minimal” image representation in terms of the topological characterization of a given 2D grayscale image. Based on this idea, we further describe our hierarchical texture aware image segmentation algorithm and compare its segmentation output and the “minimal” image representation.
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Notes
More images and segmentation results can be found at: http://prip.tuwien.ac.at/research/scis_results.zip.
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We thank both referees for their valuable comments and suggestions.
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Author was partially supported by IMUS and Spanish Ministry under grant MTM2015-67072-P (MINECO/FEDER, UE).
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Cerman, M., Janusch, I., Gonzalez-Diaz, R. et al. Topology-based image segmentation using LBP pyramids. Machine Vision and Applications 27, 1161–1174 (2016). https://doi.org/10.1007/s00138-016-0795-1
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DOI: https://doi.org/10.1007/s00138-016-0795-1