Stochastic model for curvilinear structure reconstruction using morphological profiles

Seong-Gyun Jeong 1 Yuliya Tarabalka 2 Josiane Zerubia 1
2 TITANE - Geometric Modeling of 3D Environments
CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : In this work, we propose a stochastic model for curvilinear structure reconstruction using morphological profiles of path opening operator. We apply the support vector machine classifier to obtain initial probabilities to belong to line network for each pixel. Then, we formulate a stochastic optimization problem that detects line segments corresponding to the latent curvilinear structure in a scene. Experimental results on DNA filament and remote sensing images validate the effectiveness of the proposed algorithm when compared to other recent methods.
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https://hal.inria.fr/hal-01152932
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Seong-Gyun Jeong, Yuliya Tarabalka, Josiane Zerubia. Stochastic model for curvilinear structure reconstruction using morphological profiles. ICIP 2015 - IEEE International Conference on Image Processing, Sep 2015, Quebec City, Canada. IEEE. 〈hal-01152932〉

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