SCALED AND ROTATED TEXTURE CLASSIFICATION USING A CLASS OF BASIS FUNCTIONS

• Published in: Pattern recognition Vol. 31; no. 12; pp. 1937 - 1948
• Main Authors: MANIAN, VIDYA, VÁSQUEZ, RAMÓN
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01-12-1998; Elsevier Science
• Subjects: Algorithmics. Computability. Computer arithmetics; Applied sciences; Artificial intelligence; Biorthogonal basis; Computer science; control theory; systems; Daubechies wavelets; Exact sciences and technology; Gabor non-orthogonal basis; Haar basis; Invariant texture classification; Multiresolution analysis; Orthogonal basis; Pattern recognition. Digital image processing. Computational geometry; Scaled and rotated textures; Theoretical computing; Daubechies wavelets; Haar basis; Gabor non-orthogonal basis; Invariant texture classification; Orthogonal basis; Scaled and rotated textures; Biorthogonal basis; Multiresolution analysis; Gabor filter; Texture analysis; Algorithm performance; Segmentation; Image processing; Classification; Algorithm; Pattern extraction
• ISSN: 0031-3203; 1873-5142
• DOI: 10.1016/S0031-3203(98)00053-3

Three classes of basis functions are considered for classifying scaled and rotated textured images. The first is the orthonormal, compactly supported Daubechies and the discrete Haar bases, the second is the biorthogonal basis and the third is the non orthogonal Gabor basis. Textures are scaled and rotated and the basis functions are used to expand them. Features are computed on a combination of inter-resolution coefficients. Experimental results show that the Daubechies orthonormal basis perform well in recognizing transformed textures, followed by the Haar basis. The concept of multiresolution representation and orthogonality are shown to be useful for invariant texture classificaiton.