An improved ASIFT algorithm for matching repeated patterns
Christopher Le Brese, Ju Jia Zou, Brian Uy · 2010
Image matching is a well researched topic of computer vision. Several new algorithms have been developed in recent times to deal with repetitive pattern matching and affine invariant matching. This paper presents two improvements over the state-of-the-art Affine-Scale Invariant Feature Transform (ASIFT) algorithm. The first improvement enables ASIFT to match repetitive patterns through the use of Graph Transformation Matching. The second increases the accuracy of matching by estimating the transformation between views more precisely. Results show that the proposed method is able to successfully match repetitive patterns such as the checkerboard. An increase in the number of matches can also be seen for matching views under severe affine transformations or projections.