Texture classification and segmentation using wavelet packet frame and Gaussian mixture model

DOI10.1016/j.patcog.2006.09.012zbMath1158.68472OpenAlexW2049893410MaRDI QIDQ866682

Soo Chang Kim, Tae Jin Kang

Publication date: 14 February 2007

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2006.09.012

zbMATH Keywords

texture classificationtexture segmentationGaussian mixture modelKullback--Leibler divergencefabric defect detectionwavelet packet frame

Mathematics Subject Classification ID

Pattern recognition, speech recognition (68T10)

Related Items (2)

Multi-level pixel-based texture classification through efficient prototype selection via normalized cut ⋮ Fuzzy Gaussian mixture models

Cites Work

• Computational models of visual neurons specialised in the detection of periodic and aperiodic oriented visual stimuli: bar and grating cells
• A theory for multiresolution signal decomposition: the wavelet representation
• Orthonormal bases of compactly supported wavelets
• A Comparative Study of Texture Measures for Terrain Classification
• Entropy-based algorithms for best basis selection
• An adaptive approach to unsupervised texture segmentation using \(M\)-band wavelet transform
• Unnamed Item

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