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This article is cited in 6 scientific papers (total in 6 papers)
IMAGE PROCESSING, PATTERN RECOGNITION
Study of informative feature selection approaches for the texture image recognition problem using the Laws’ masks
V. V. Kutikovaa, A. V. Gaidelba a Samara State Aerospace University, Samara, Russia
b Image Processing Systems Institute, Russian Academy of Sciences, Samara, Russia
Abstract:
In the paper, the efficiency of two methods for feature selection based on Laws’ masks is studied. These are a method of feature ordering in accordance with the criterion of discriminant analysis and tstatistic and a method of iterations through all pairs and triplets of features. The experimental results show that the classification error of the best group for features based on the standard deviation does not exceed the classification error of the best group for features based on the average energy.
Keywords:
texture analysis, Laws’ masks, feature selection, criterion of discriminant analysis, t-statistic.
Received: 27.10.2015 Revised: 22.11.2015
Citation:
V. V. Kutikova, A. V. Gaidel, “Study of informative feature selection approaches for the texture image recognition problem using the Laws’ masks”, Computer Optics, 39:5 (2015), 744–750
Linking options:
https://www.mathnet.ru/eng/co40 https://www.mathnet.ru/eng/co/v39/i5/p744
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Abstract page: | 205 | Full-text PDF : | 78 | References: | 69 |
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