A Contour Angle Orientation for Power Equipment Infrared and Visible Image Registration

Abstract

Automatic registration for infrared, and visible images of power equipment has become a challenging work in intelligent diagnosis system of the power grid. Existing registration methods usually fail in accurately aligning power equipment infrared, and visible images because of resolutions, spectrums, and viewpoints differences. To solve this problem, we propose a novel main orientation of feature points named contour angle orientation (CAO), and describe an automatic infrared, and visible image registration method named CAO-Coarse to Fine (CAO-C2F). CAO is based on the contour feature of images, and invariant to images viewpoints, and scales differences. C2F is a feature matching method to obtain correct matches. Our proposed CAO-C2F method includes four steps. First, feature points in contours are extracted by the curvature scale space (CSS) corner detector based on local, and global curvature. Second, the CAO of each feature point is computed as the main orientation. Third, modified scale-invariant feature transform (SIFT) descriptors on the main orientations are extracted, and matched by bilateral matching. Finally, accurate matches are obtained by applying the C2F method. Registration experiments on a self-established images dataset show our proposed CAO-C2F method accurately aligns images, and outperforms other state-of-arts in terms of precision, recall, and root-mean-square error.