Image texture classification using quadrature mirror filter bank in combination with co-occurrence matrices

Thor Ole Gulsrud; John Hakon Husoy

doi:10.1117/12.186562

21 September 1994 Image texture classification using quadrature mirror filter bank in combination with co-occurrence matrices

Thor Ole Gulsrud, John Hakon Husoy

Author Affiliations +

Proceedings Volume 2298, Applications of Digital Image Processing XVII; (1994) https://doi.org/10.1117/12.186562
Event: SPIE's 1994 International Symposium on Optics, Imaging, and Instrumentation, 1994, San Diego, CA, United States

Abstract

This paper presents a method for the classification of textures using quadrature mirror filter (QMF) bank subband decomposition in combination with statistical descriptors. In our combined method the QMF bank splits the input image into four subbands, and statistical descriptors based on co-occurrence matrices are computed from the subsampled low-low band. The experiments demonstrate that the combined method has better classification performance than that of statistical descriptors computed from the co-occurrence matrices of the whole texture image. In addition, the experiments demonstrate that the combined method based on computationally efficient IIR QMF banks yields approximately the same classification results as the combined method based on classical FIR QMF banks.

Citation Download Citation

Thor Ole Gulsrud and John Hakon Husoy "Image texture classification using quadrature mirror filter bank in combination with co-occurrence matrices", Proc. SPIE 2298, Applications of Digital Image Processing XVII, (21 September 1994); https://doi.org/10.1117/12.186562

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