Real-time Image Registration with Region Matching

Image registration, the task of aligning two images, is a fundamental operation for applications like image stitching or image comparison. In our project in surveillance for route clearance operations, a drone will be used to detect suspicious people and vehicles. This paper presents an approach for real-time image alignment of video images acquired by a moving camera. The high correlation between successive images allows for relatively simple algorithms. We considered region segmentation as an alternative to the more classical corner or interest point detectors and evaluated the appropriateness of connected component labeling with a connectivity defined by the gray-level similarity between neighboring pixels. Real-time processing is intended thanks to a very fast segment-based (as opposed to pixel-based) connected component labeling. The regions, even if not always pleasing the human eye, proved stable enough to be linked across images by trivial features such as the area and the centroid. The vector shifts between matching regions were filtered and modeled by an affine transform. The paper discusses the execution time obtained by this feasibility study for all the steps needed for image registration and indicates the planned improvements to achieve real-time.