Topology-based image segmentation using LBP pyramids

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 charact...

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Bibliographic Details
Published in:Machine vision and applications 2016-11, Vol.27 (8), p.1161-1174
Main Authors: Cerman, Martin, Janusch, Ines, Gonzalez-Diaz, Rocio, Kropatsch, Walter G.
Format: Article
Language:English
Subjects:
Algorithms
Codification
Combinatorial analysis
Communications Engineering
Computer Science
Image Processing and Computer Vision
Image segmentation
Markov analysis
Networks
Pattern Recognition
Pyramids
Representations
Special Issue Paper
Surface layer
Texture
Topology
Vision systems
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Summary: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.
ISSN:0932-8092
1432-1769
DOI:10.1007/s00138-016-0795-1