Detecting Irregular Curvilinear Structures in Gray Scale and Color Imagery Using Multi-directional Oriented Flux

Engin Turetken, Carlos Becker, Przemyslaw Glowacki, Fethallah Benmansour, Pascal Fua; Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2013, pp. 1553-1560

Abstract


We propose a new approach to detecting irregular curvilinear structures in noisy image stacks. In contrast to earlier approaches that rely on circular models of the crosssections, ours allows for the arbitrarily-shaped ones that are prevalent in biological imagery. This is achieved by maximizing the image gradient flux along multiple directions and radii, instead of only two with a unique radius as is usually done. This yields a more complex optimization problem for which we propose a computationally efficient solution. We demonstrate the effectiveness of our approach on a wide range of challenging gray scale and color datasets and show that it outperforms existing techniques, especially on very irregular structures.

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[bibtex]
@InProceedings{Turetken_2013_ICCV,
author = {Turetken, Engin and Becker, Carlos and Glowacki, Przemyslaw and Benmansour, Fethallah and Fua, Pascal},
title = {Detecting Irregular Curvilinear Structures in Gray Scale and Color Imagery Using Multi-directional Oriented Flux},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
month = {December},
year = {2013}
}