Aligned matching: An efficient image matching technique

Local feature based methods have achieved a great success in the field of image matching due to its invariance under typical image transformations. However, local features are often not invariant under complex non-affine transformations, which makes the matching methods ineffective. To remove the effect of complex image transformations, this paper proposes alignment of images before they are compared. An automatic image alignment method is introduced based on thin plate spline (TPS) warping. Then, the aligned matching scheme is designed to utilize correct alignments and reject false alignments for the improvement of matching performance. The method is evaluated using scene retrieval and object categorization. Experiments show the proposed aligned matching outperforms two typical methods: voting scheme and histograms comparison (over a set of prototypes which must be found by clustering).