Open Access
17 March 2014 Morphological segmentation approaches of directional structures based on connections
Carlos A. Paredes-Orta, Jorge D. Mendiola-Santibanez, Ana M. Herrera-Navarro, Luis A. Morales-Hernandez, Ivan Terol-Villalobos
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Abstract
The multiscale morphological approaches for segmenting directional structures are proposed. First, the use of the composition of connections to extract the directional structures of the image is investigated. We show that even though the composition of connectivities enables the correct determination of the main directional structures, the requirement of the scales for segmenting the image makes this algorithm more or less complex to apply. Then, a morphological image segmentation approach is proposed based on the concept of connectivity in a viscous lattice sense. Two functions are computed to characterize the directional structures: viscosity and orientation. The viscosity function codifies the different scales of the structure and is computed from the supremum of directional erosions. This function contains the sizes of the longest lines that can be included in the structure. To determine the directions of the line segments, the orientation function is employed. By combining both images—viscosity and orientation functions— an orientation partition function is created. This last function contains information of the maxima of the viscosity function and their orientation. Finally, the elements of the orientation partition function are merged according to some criteria, using a histogram-based segmentation approach to compute an optimal partition.
CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
Carlos A. Paredes-Orta, Jorge D. Mendiola-Santibanez, Ana M. Herrera-Navarro, Luis A. Morales-Hernandez, and Ivan Terol-Villalobos "Morphological segmentation approaches of directional structures based on connections," Journal of Electronic Imaging 23(2), 023007 (17 March 2014). https://doi.org/10.1117/1.JEI.23.2.023007
Published: 17 March 2014
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CITATIONS
Cited by 1 scholarly publication.
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KEYWORDS
Image segmentation

Image processing algorithms and systems

Image filtering

Image processing

Binary data

Mathematical morphology

Digital filtering

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