IJPAM: Volume 119, No. 1 (2018)

Title

COMPARATIVE ANALYSIS OF
POLYNOMIAL FEATURES FOR TEXTURE CLASSIFICATION

Authors

Ahmad M. Alenezi$^1$, I.S. Rakhimov$^2$
$^1$Department of Mathematics
The Higher Institute of Telecommunication and Navigation
PAAET, Shuwaikh, KUWAIT
$^{1,2}$Department of Mathematics
Faculty of Science and Institute for Mathematical Research Universiti Putra Malaysia
UPM Serdang Selangor D.E., MALAYSIA

Abstract

In the paper the feature extraction capability of Krawtchouk and Chebyshev polynomials are tested using Kylberg texture set. The original feature extraction technique based on the combination of either Chebyshev or Krawtchouk moments and low order statistical moments is proposed. Among possible configurations of statistical moments, the most suitable for each type of polynomial moments are chosen. Support Vector Machine is used as primary classification method.

History

Received: 2017-05-29
Revised: 2017-06-06
Published: June 5, 2018

AMS Classification, Key Words

AMS Subject Classification: 00A69
Key Words and Phrases: texture, features, SVM, classification

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Bibliography

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How to Cite?

DOI: 10.12732/ijpam.v119i1.8 How to cite this paper?

Source:
International Journal of Pure and Applied Mathematics
ISSN printed version: 1311-8080
ISSN on-line version: 1314-3395
Year: 2018
Volume: 119
Issue: 1
Pages: 99 -


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