Affiliations: Electronics and Telecommunication department, College
of Engineering Pune, India, Shivajinagar Pune-411005. vsv@extc.coep.org.in;
ppr@extc.coep.org.in
Note: [] Address for correspondence: Electronics and telecommunication
Department, College of Engineering Pune, India
Abstract: In this paper, geometric invariant texture analysis, which comprises
of rotation, scale and translation (RST) invariance, is presented. Many types
of moments and functions of moments have been utilized in RST invariant pattern
recognition applications. However, use of moments for texture content-based
image analysis is limited. Here, application of Zernike moment for geometric
invariant texture analysis is studied. An algorithm is proposed to design fast
and modified Zernike moments to extract a particular texture from image
irrespective of its rotation scale change and translation. The algorithm is
tested for its robustness in the presences of various noises like salt and
paper, Gaussian and speckle noise. The operator is evaluated for computation of
moments on different data sets of textures like Brodatz and Vistex. Comparison
is done with traditional Zernike moments based techniques, Fast Fourier
Transform (FFT)-Zernike moments based technique and proposed modified Zernike
moment based technique.
Keywords: Texture analysis, geometric transforms, Zernike moments, Fast Fourier Transform
