Performance evaluation of texture measures with classification based on Kullback discrimination of distributions

This paper evaluates the performance both of some texture measures which have been successfully used in various applications and of some new promising approaches. For classification a method based on Kullback discrimination of sample and prototype distributions is used. The classification results fo...

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Bibliographic Details
Published inPattern Recognition, 1994 12th International Conference On. Vol. 1 Vol. 1; pp. 582 - 585 vol.1
Main Authors Ojala, T., Pietikainen, M., Harwood, D.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1994
Subjects
Analysis of variance
Autocorrelation
Automation
Distributed computing
Electric variables measurement
Histograms
Image texture analysis
Performance evaluation
Prototypes
Rotation measurement
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ISBN0818662654
9780818662652
DOI10.1109/ICPR.1994.576366

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Summary:This paper evaluates the performance both of some texture measures which have been successfully used in various applications and of some new promising approaches. For classification a method based on Kullback discrimination of sample and prototype distributions is used. The classification results for single features with one-dimensional feature value distributions and for pairs of complementary features with two-dimensional distributions are presented.
ISBN:0818662654
9780818662652
DOI:10.1109/ICPR.1994.576366