Extracting Line Parameters of Woven Wire Mesh in Images under Directional Illumination

Abstract

Localizing the wires of a mesh in an image is important in various image processing applications. This task can be difficult if the wires cannot be detected with simple line detectors, e.g. if corrugated wires of a woven mesh appear as dark and bright segments under directional illumination. Template matching is insufficient if the appearance of the wires varies throughout the image, depending on the viewing angle, and neural networks require computationally expensive training on a well-prepared dataset. We propose an efficient way to extract the line parameters (position and orientation) of the wires of a regular mesh from an image by finding meaningful local minima of a cost function, followed by RANSAC-controlled robust outlier filtering.