  This work shows the use of a two-dimensional Gabor wavelets in image
processing. Convolution with such a two-dimensional wavelet can be separated
into two series of one-dimensional ones. The key idea of this work is to
utilize a Gabor wavelet as a multiscale partial differential operator of a
given order. Gabor wavelets are used here to detect edges, corners and blobs. A
performance of such an interest point detector is compared to detectors
utilizing a Haar wavelet and a derivative of a Gaussian function. The proposed
approach may be useful when a fast implementation of the Gabor transform is
available or when the transform is already precomputed.
