Multimodal Image Registration With Line Segments by Selective Search

This paper proposes a line segment-based image registration method. Edges are detected from images by a modified Canny operator, and line segments are then extracted from these edges. At registration, triplets (quaternions) of line segment correspondences are tentatively formed by applying the distance and orientation constraints, which determine an intermediate transformation. Those triplets (quaternions) of lines resulting in higher similarity metrics are preserved, and their intersections are refined by an iterative process or random sample consensus. The proposed method is tested on indoor and outdoor EO/IR image pairs, and the average registration error is calculated to be compared with existing algorithms. Experimental results show that the proposed registration method can robustly align EO/IR images containing line segments, providing more reliable and accurate registration results on multimodal images.