On scaled and rotated texture segmentation using a class of basis functions

In this paper three classes of basis functions are considered for segmenting scaled and rotated textured images. The first is the orthonormal, compactly supported Daubechies and the discrete Haar bases, the second class is the biorthogonal basis and the third is the non orthogonal Gabor basis. Texture operators are constructed from the bases functions based on the notion of multiresolution analysis. The textures are scaled and rotated and the basis functions are used to expand them. Certain features are computed on the expansions and used by a classifier to recognize and subsequently segment the texture mosaics. Experimental results on different texture mosaics show that the features obtained from the Daubechies, biorthogonal basis perform well in recognizing transformed textures. The concept of multiresolution representation is shown to be useful for invariant texture segmentation.