Thick Line Segment Detection with Fast Directional Tracking

Philippe Even (1, 2) , Phuc Ngo (1, 2) , Bertrand Kerautret (3, 2)

1 LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
2 ADAGIO - Applying Discrete Algorithms to Genomics and Imagery
3 imagine - Extraction de Caractéristiques et Identification

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.

Mots clés: Line/segment detection; Discrete objects; Digital geometry

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]; Traitement des images [eess.IV]

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⟩