Progressive Tree-like Curvilinear Structure Reconstruction with Structured Ranking Learning and Graph Algorithm

Abstract

We propose a novel tree-like curvilinear structure reconstruction algorithm based on supervised learning and graph theory. In this work we analyze image patches to obtain the local major orientations and the rankings that correspond to the curvilinear structure. To extract local curvilinear features, we compute oriented gradient information using steerable… (More)

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Cite this paper

@article{Jeong2016ProgressiveTC, title={Progressive Tree-like Curvilinear Structure Reconstruction with Structured Ranking Learning and Graph Algorithm}, author={Seong-Gyun Jeong and Yuliya Tarabalka and Nicolas Nisse and Josiane Zerubia}, journal={CoRR}, year={2016}, volume={abs/1612.02631} }