Wavelet based Shape Descriptors using Morphology for Texture Classification

1
P.Kiran Kumar Reddy
P.Kiran Kumar Reddy
2
Vakulabharanam Vijaya Kumar
Vakulabharanam Vijaya Kumar
3
B. Eswara Reddy
B. Eswara Reddy
1 rgmcet/JNTUA

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The present paper is an extension of our previous paper [1]. In this paper shape descriptors are derived on binary cross diagonal texture matrix (BCDTM) after formation of morphological gradient on the wavelet domain. Morphological gradient is obtained from the difference of dilated and eroded gray level texture. A close relationship can be obtained with contour and texture pattern by evaluating morphological edge information. Morphological operations are simple and they provide topology of the texture, that is the reason the proposed morphological gradient provides abundance of texture and shape information. The proposed Wavelet based morphological gradient binary cross diagonal shape descriptors texture matrix (WMG-BCDSDTM) using wavelets is experimented on wide range of textures for classification purpose. The experimental results indicate a high classification rate.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

P.Kiran Kumar Reddy. 2014. \u201cWavelet based Shape Descriptors using Morphology for Texture Classification\u201d. Global Journal of Computer Science and Technology - G: Interdisciplinary GJCST-G Volume 14 (GJCST Volume 14 Issue G1): .

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GJCST Volume 14 Issue G1
Pg. 21- 27
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Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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August 12, 2014

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English

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The present paper is an extension of our previous paper [1]. In this paper shape descriptors are derived on binary cross diagonal texture matrix (BCDTM) after formation of morphological gradient on the wavelet domain. Morphological gradient is obtained from the difference of dilated and eroded gray level texture. A close relationship can be obtained with contour and texture pattern by evaluating morphological edge information. Morphological operations are simple and they provide topology of the texture, that is the reason the proposed morphological gradient provides abundance of texture and shape information. The proposed Wavelet based morphological gradient binary cross diagonal shape descriptors texture matrix (WMG-BCDSDTM) using wavelets is experimented on wide range of textures for classification purpose. The experimental results indicate a high classification rate.

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Wavelet based Shape Descriptors using Morphology for Texture Classification

P.Kiran Kumar Reddy
P.Kiran Kumar Reddy rgmcet/JNTUA
Vakulabharanam Vijaya Kumar
Vakulabharanam Vijaya Kumar
B. Eswara Reddy
B. Eswara Reddy

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