Symbolic pixel labeling for curvilinear feature detection

doi:10.1016/0167-8655(88)90079-7

Pattern Recognition Letters

Volume 8, Issue 5, December 1988, Pages 299-310

https://doi.org/10.1016/0167-8655(88)90079-7 Get rights and content

Abstract

This paper describes a method of detecting thin curvilinear features in an image based on a detailed analysis of the local gray level patterns at each pixel. This allows operations such as thinning and gap filling to be based on more accurate information.

References (4)

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Digital Picture Processing
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Mask matching for linear feature detection

There are more references available in the full text version of this article.

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^☆: The support of the Defense Mapping Agency under Contract DMA-85-C-0007 is gratefully acknowledged, as is the help of Sandy German in preparing this paper.

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Pattern Recognition Letters

Symbolic pixel labeling for curvilinear feature detection☆

Abstract

Digital Picture Processing

Mask matching for linear feature detection

Oriented connectivity-based method for segmenting solar loops

Robust detection of straight and circular road segments in noisy aerial images

Automated detection of solar loops by the oriented connectivity method

Lineal feature detection of rural imagery using multiresolution filters

Building of symbolic hierarchical graphs for feature extraction

Geometrical approach for corner detection