Novel phase-based descriptor using bispectrum for texture classification

In this paper, we propose a novel rotation invariant and noise tolerant descriptor for texture classification. This descriptor is based on circular statistics of Fourier phase. This one is recovered from the third order spectrum namely the bispectrum, known to provide invariance properties and to preserve phase information. The computational complexity of two dimensional image is reduced using Radon transform. At first, the input image is decomposed into a set of 1D radon projections. Then, for each projection the bispectrum is computed and the phase vector is recovered. Features vectors contain circular statistics of each phase vector recovered from bispectrum of each 1D projection. The proposed descriptor is evaluated on three test suites from the database “Outex” and compared with three descriptors also based on the phase. According to the classification experiments, our descriptor achieves highest rates under noise, illumination and rotation changes.