Study of Feature based Image Registration Algorithms for Navigation of Unmanned Aerial Vehicles

Image registration is an important preprocessing step for computer vision tasks such as object recognition by a robot or change detection over a natural terrain from satellite images. This paper discusses the basic steps for the feature based image registration, and surveys the various methodologies from literature applicable for each step. The evolution of algorithms on image features is explained with some of their mathematical concepts, along with their limitations. Two videos captured from an unmanned aerial vehicle were used for experimentation. The performance of intensity based image registration using normalized cross correlation and Speeded Up Robust Features was observed by registering various frames of the videos. Intensity based methods perform well for all type of images when the images to be registered vary by only a translation. Feature based methods are suitable when the possible transformation between the images are unknown. Feature based methods fail when the images lack distinct features such as corner points. The study presented would enable one to choose the right methodology for each step of the image registration algorithm, for various real time computer vision applications such as navigation of unmanned aerial vehicles.