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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Published in | Pattern Recognition, 1994 12th International Conference On. Vol. 1 Vol. 1; pp. 582 - 585 vol.1 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
1994
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Subjects | |
Online Access | Get full text |
ISBN | 0818662654 9780818662652 |
DOI | 10.1109/ICPR.1994.576366 |
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Abstract | 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. |
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AbstractList | 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. |
Author | Pietikainen, M. Harwood, D. Ojala, T. |
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PublicationTitle | Pattern Recognition, 1994 12th International Conference On. Vol. 1 |
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Snippet | This paper evaluates the performance both of some texture measures which have been successfully used in various applications and of some new promising... |
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StartPage | 582 |
SubjectTerms | Analysis of variance Autocorrelation Automation Distributed computing Electric variables measurement Histograms Image texture analysis Performance evaluation Prototypes Rotation measurement |
Title | Performance evaluation of texture measures with classification based on Kullback discrimination of distributions |
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