Wavelet based corner detection using singular value decomposition

In this paper we present a novel technique for wavelet-based corner detection using singular value decomposition (SVD). Here SVD facilitates the selection of global natural scale in the discrete wavelet transform. We define natural scale as the level associated with most prominent (dominant) eigenvalue. The eigenvector corresponding to the dominant eigenvalue is considered as the natural scale. The corners are detected at the locations corresponding to modulus maxima. Results show the suitability of the approach. Comparison with a recently proposed technique is also provided.