Abstract: By comparing with some common approached of feature extraction and matching, the paper proposes an improved method of feature extraction and matching for image mosaic which improves image quality and processing speed. It uses scale invariant feature transform (SIFT) to extract invariant features from images, approximate nearest neighbor searching and random sample consensus (RANSAC) to perform reliable matching. Parameters of the transformation between images are obtained from the matched feature points to realize image stitching and blending. The feature points are invariant to affine transformation, noise contamination and illumination variation, leading to robustness of the method. Experimental results show that the proposed method is fast and can produce high quality image mosaic.

Key words:

image mosaic, scale invariant feature transform , approximate nearest neighbor matching, random sample consensus (RANSAC)