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Proceedings Paper

Detecting curvilinear structure using ridge distribution feature and layer growth method
Author(s): Ge Gao; Guoyou Wang; Yu Shi
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Paper Abstract

Wide line detection plays an important role in image analysis and computer vision. However, most of the existing algorithms focus on the extraction of the line positions and length, ignoring line thickness and direction which can deepen our understanding of images. This paper presents a novel wide line detector using the ridge distribution feature and layer growth method. Unlike most existing edge and line detectors which use directional derivatives, our proposed method extracts the ridge target point and use the layer growth to find the line completely based on the isotropic nonlinear filter. Ridge points are detected by its distribution symmetry based on the isotropic responses via circular masks and orientation of the ridge is determined roughly. The ridge point is selected as a seed point, then growth layer by layer, to determine the width and orientation of the curvilinear structure accurately. Instead of point by point scanning, we label points in the growth region and adjust the scanning step adaptively which improve the method efficiently. The proposed method can detect the accurate width and direction of lines dynamically. This can provide great convenience for post-processing or for application requirements. A sequence of tests on a variety of image samples demonstrates that the proposed method outperforms state-of-the-art methods.

Paper Details

Date Published: 26 October 2013
PDF: 8 pages
Proc. SPIE 8918, MIPPR 2013: Automatic Target Recognition and Navigation, 891812 (26 October 2013); doi: 10.1117/12.2032748
Show Author Affiliations
Ge Gao, Huazhong Univ. of Science and Technology (China)
Guoyou Wang, Huazhong Univ. of Science and Technology (China)
Yu Shi, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 8918:
MIPPR 2013: Automatic Target Recognition and Navigation
Tianxu Zhang; Nong Sang, Editor(s)

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