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Texture Based Pattern Classification

by R.J.Bhiwani, S.M.Agrawal, M.A.Khan
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 1 - Number 1
Year of Publication: 2010
Authors: R.J.Bhiwani, S.M.Agrawal, M.A.Khan
10.5120/21-129

R.J.Bhiwani, S.M.Agrawal, M.A.Khan . Texture Based Pattern Classification. International Journal of Computer Applications. 1, 1 ( February 2010), 54-56. DOI=10.5120/21-129

@article{ 10.5120/21-129,
author = { R.J.Bhiwani, S.M.Agrawal, M.A.Khan },
title = { Texture Based Pattern Classification },
journal = { International Journal of Computer Applications },
issue_date = { February 2010 },
volume = { 1 },
number = { 1 },
month = { February },
year = { 2010 },
issn = { 0975-8887 },
pages = { 54-56 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume1/number1/21-129/ },
doi = { 10.5120/21-129 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:43:39.924443+05:30
%A R.J.Bhiwani
%A S.M.Agrawal
%A M.A.Khan
%T Texture Based Pattern Classification
%J International Journal of Computer Applications
%@ 0975-8887
%V 1
%N 1
%P 54-56
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Texture can be observed in many natural and synthetic images from multispectral satellite images to the microscopic images of cell or tissue samples. Texture is an innate property of virtually all surfaces, the grain of wood, the weave of fabric, the pattern of crop in fields etc It contains important information about the structural arrangement of surfaces and their relationship to the surrounding environment. Since the textural properties of images appear to carry useful information, for discriminating purpose features have always been calculated for textures.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Texture pattern classification DWT Euclidean distance Bray Curtis distance Manhattan distance Canberra distance

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