Detection and matching of curvilinear structures

  • Authors:

  • C. Lemaitre;M. Perdoch;A. Rahmoune;J. Matas;J. Miteran

  • Affiliations:

  • Laboratoire d'électronique, d'informatique et de l'image, LE2I, Faculté Mirande, Université de Bourgogne, 21000 Dijon, France;The Center for Machine Perception, Faculty of Electrical Engineering, Czech Technical University, Technicka 2, 166 27 Prague 6, Czech Republic;Laboratoire d'électronique, d'informatique et de l'image, LE2I, Faculté Mirande, Université de Bourgogne, 21000 Dijon, France;The Center for Machine Perception, Faculty of Electrical Engineering, Czech Technical University, Technicka 2, 166 27 Prague 6, Czech Republic;Laboratoire d'électronique, d'informatique et de l'image, LE2I, Faculté Mirande, Université de Bourgogne, 21000 Dijon, France

  • Venue:
  • Pattern Recognition
  • Year:
  • 2011

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Abstract

We propose an approach to curvilinear and wiry object detection and matching based on a new curvilinear region detector (CRD) and a shape context-like descriptor (COH). Standard methods for local patch detection and description are not directly applicable to wiry objects and curvilinear structures, such as roads, railroads and rivers in satellite and aerial images, vessels and veins in medical images, cables, poles and fences in urban scenes, stems and tree branches in natural images, since they assume the object is compact, i.e. that most elliptical patches around features cover only the object. However, wiry objects often have no flat parts and most neighborhoods include both foreground and background. The detection process is first evaluated in terms of segmentation quality of curvilinear regions. The repeatability of the detection is then assessed using the protocol introduced in Mikolajczyk et al. [1]. Experiments show that the CRD is at least as robust as to several image acquisition conditions changes (viewpoint, scale, illumination, compression, blur) as the commonly used affine-covariant detectors. The paper also introduces an image collection containing wiry objects and curvilinear structures (the W-CS dataset).