Abstract
A novel method based on empirical mode decomposition (EMD) is introduced in this paper for the detection of affine invariant interest or feature points. The proposed algorithm is a contour based method, where image edges are first detected by utilizing morphological operators followed by an edge thinning process and then the corner or interest points are identified based on the local curvature of the edges. In this work a novel method based on 1-D EMD is formulated to select good discriminative interest points from the edges. The proposed method is compared with four existing approaches that yield good results. The performance is evaluated by employing a criteria known as repeatability rate, which evaluates the geometric stability of an interest point detector under different transformations. The results prove the efficacy and superiority of the proposed technique over other schemes in terms of detecting more true corner points.
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