Абстрактный

A Comparison of SIFT and SURF

P M Panchal, S R Panchal, S K Shah

Accurate, robust and automatic image registration is critical task in many applications. To perform image registration/alignment, required steps are: Feature detection, Feature matching, derivation of transformation function based on corresponding features in images and reconstruction of images based on derived transformation function. Accuracy of registered image depends on accurate feature detection and matching. So these two intermediate steps are very important in many image applications: image registration, computer vision, image mosaic etc. This paper presents two different methods for scale and rotation invariant interest point/feature detector and descriptor: Scale Invariant Feature Transform (SIFT) and Speed Up Robust Features (SURF). It also presents a way to extract distinctive invariant features from images that can be used to perform reliable matching between different views of an object/scene.