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Detection of Curved Lines with B-COSFIRE Filters: A Case Study on Crack Delineation

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Book cover Computer Analysis of Images and Patterns (CAIP 2017)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10424))

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Abstract

The detection of curvilinear structures is an important step for various computer vision applications, ranging from medical image analysis for segmentation of blood vessels, to remote sensing for the identification of roads and rivers, and to biometrics and robotics, among others. This is a nontrivial task especially for the detection of thin or incomplete curvilinear structures surrounded with noise. We propose a general purpose curvilinear structure detector that uses the brain-inspired trainable B-COSFIRE filters. It consists of four main steps, namely nonlinear filtering with B-COSFIRE, thinning with non-maximum suppression, hysteresis thresholding and morphological closing. We demonstrate its effectiveness on a data set of noisy images with cracked pavements, where we achieve state-of-the-art results (F-measure \(=0.865\)). The proposed method can be employed in any computer vision methodology that requires the delineation of curvilinear and elongated structures.

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Authors and Affiliations

  1. Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, Groningen, The Netherlands

    Nicola Strisciuglio, George Azzopardi & Nicolai Petkov

  2. Intelligent Computer Systems, University of Malta, Msida, Malta

    George Azzopardi

Authors
  1. Nicola Strisciuglio
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  2. George Azzopardi
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  3. Nicolai Petkov
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Corresponding author

Correspondence to Nicola Strisciuglio .

Editor information

Editors and Affiliations

  1. Linköping University, Linköping, Sweden

    Michael Felsberg

  2. Lund University, Lund, Sweden

    Anders Heyden

  3. University of Southern Denmark, Odense, Denmark

    Norbert Krüger

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Strisciuglio, N., Azzopardi, G., Petkov, N. (2017). Detection of Curved Lines with B-COSFIRE Filters: A Case Study on Crack Delineation. In: Felsberg, M., Heyden, A., Krüger, N. (eds) Computer Analysis of Images and Patterns. CAIP 2017. Lecture Notes in Computer Science(), vol 10424. Springer, Cham. https://doi.org/10.1007/978-3-319-64689-3_9

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  • DOI: https://doi.org/10.1007/978-3-319-64689-3_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64688-6

  • Online ISBN: 978-3-319-64689-3

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