Automated classification of crystallisation experiments using wavelets and statistical texture characterisation techniques

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A method is presented for the classification of protein crystallization images based on image decomposition using the wavelet transform. The distribution of wavelet coefficient values in each sub-band image is modelled by a generalized Gaussian distribution to provide discriminatory variables. These statistical descriptors, together with second-order statistics obtained from joint probability distributions, are used with learning vector quantization to classify protein crystallization images.
Original languageEnglish
Pages (from-to)8-17
Number of pages10
JournalJournal of Applied Crystallography
Issue number1
Publication statusPublished - 1 Apr 2008


  • classification;
  • pattern recognition;
  • crystallization images;
  • wavelet transform;
  • statistical descriptors

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