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Thick Line Segment Detection with Fast Directional Tracking

Philippe Even 1, 2 Phuc Ngo 1, 2 Bertrand Kerautret 3, 2
2 ADAGIO - Applying Discrete Algorithms to Genomics and Imagery
LORIA - ALGO - Department of Algorithms, Computation, Image and Geometry
3 imagine - Extraction de Caractéristiques et Identification
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : This paper introduces a fully discrete framework for a new straight line detector in gray-level images, where line segments are enriched with a thickness parameter intended to provide a quality criterion on the extracted feature. This study is based on a previous work on interactive line detection in gray-level images. At first, a better estimation of the segment thickness and orientation is achieved through two main improvements: adaptive directional scans and control of assigned thickness. Then, these advances are exploited for a complete unsupervised detection of all the line segments in an image. The new thick line detector is left available in an online demonstration.
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Contributor : Bertrand Kerautret <>
Submitted on : Tuesday, October 8, 2019 - 11:48:05 AM
Last modification on : Monday, December 28, 2020 - 2:23:01 PM


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Philippe Even, Phuc Ngo, Bertrand Kerautret. Thick Line Segment Detection with Fast Directional Tracking. ICIAP 2019 -20th International Conference on Image Analysis and Processing, Sep 2019, trento, Italy. pp.159-170, ⟨10.1007/978-3-030-30645-8_15⟩. ⟨hal-02189916⟩



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