Wavelet-based corner detection technique using optimal scale
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 discrete wavelet transform. We define natural scale as the level associated with most prominent (dominant) eigenvalue. Eigenvector corresponding to dominant eigenvalue is considered as the optimal scale. The corners are detected at the locations corresponding to modulus maxima. Results indicate the suitability of the approach. Comparison with a recently proposed technique is also provided.
corner detection shape analysis wavelet decomposition dyadic decomposition feature extraction