Wavelets and support vector machines for texture classification

Kashif Mahmood Rajpoot; Nasir Mahmood Rajpoot

doi:10.1109/INMIC.2004.1492898

Wavelets and support vector machines for texture classification

Kashif Mahmood Rajpoot, Nasir Mahmood Rajpoot

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We present a novel texture classification algorithm using 2-0 discrete wavelet transform (DWT) and support vector machines (SVM). The DWT is used to generate feature images from individual wavelet subbands, and a local energy function is computed corresponding to each pixel of the feature images. This feature vector is first used for training and later on for testing the SVM classifier. The experimental setup consists of images from the Brodatz and MIT VisTeX texture databases and a combination of some images therein. The proposed method produces promising classification results for both single and multiple class texture analysis problems.

Original language	English
Title of host publication	Proceedings of INMIC 2004 - 8th International Multitopic Conference
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	328-333
Number of pages	6
ISBN (Electronic)	0780386809, 9780780386808
DOIs	https://doi.org/10.1109/INMIC.2004.1492898
Publication status	Published - 2004
Event	8th International Multitopic Conference, INMIC 2004 - Lahore, Pakistan Duration: 24 Dec 2004 → 26 Dec 2004

Publication series

Name	Proceedings of INMIC 2004 - 8th International Multitopic Conference

Conference

Conference	8th International Multitopic Conference, INMIC 2004
Country/Territory	Pakistan
City	Lahore
Period	24/12/04 → 26/12/04

Bibliographical note

Publisher Copyright:
© 2004 IEEE.

ASJC Scopus subject areas

General Engineering
General Computer Science

Access to Document

10.1109/INMIC.2004.1492898

Cite this

Rajpoot, K. M., & Rajpoot, N. M. (2004). Wavelets and support vector machines for texture classification. In Proceedings of INMIC 2004 - 8th International Multitopic Conference (pp. 328-333). Article 1492898 (Proceedings of INMIC 2004 - 8th International Multitopic Conference). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/INMIC.2004.1492898

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title = "Wavelets and support vector machines for texture classification",

abstract = "We present a novel texture classification algorithm using 2-0 discrete wavelet transform (DWT) and support vector machines (SVM). The DWT is used to generate feature images from individual wavelet subbands, and a local energy function is computed corresponding to each pixel of the feature images. This feature vector is first used for training and later on for testing the SVM classifier. The experimental setup consists of images from the Brodatz and MIT VisTeX texture databases and a combination of some images therein. The proposed method produces promising classification results for both single and multiple class texture analysis problems.",

author = "Rajpoot, {Kashif Mahmood} and Rajpoot, {Nasir Mahmood}",

note = "Publisher Copyright: {\textcopyright} 2004 IEEE.; 8th International Multitopic Conference, INMIC 2004 ; Conference date: 24-12-2004 Through 26-12-2004",

year = "2004",

doi = "10.1109/INMIC.2004.1492898",

language = "English",

series = "Proceedings of INMIC 2004 - 8th International Multitopic Conference",

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Rajpoot, KM & Rajpoot, NM 2004, Wavelets and support vector machines for texture classification. in Proceedings of INMIC 2004 - 8th International Multitopic Conference., 1492898, Proceedings of INMIC 2004 - 8th International Multitopic Conference, Institute of Electrical and Electronics Engineers (IEEE), pp. 328-333, 8th International Multitopic Conference, INMIC 2004, Lahore, Pakistan, 24/12/04. https://doi.org/10.1109/INMIC.2004.1492898

Wavelets and support vector machines for texture classification. / Rajpoot, Kashif Mahmood; Rajpoot, Nasir Mahmood.
Proceedings of INMIC 2004 - 8th International Multitopic Conference. Institute of Electrical and Electronics Engineers (IEEE), 2004. p. 328-333 1492898 (Proceedings of INMIC 2004 - 8th International Multitopic Conference).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Rajpoot, Nasir Mahmood

PY - 2004

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N2 - We present a novel texture classification algorithm using 2-0 discrete wavelet transform (DWT) and support vector machines (SVM). The DWT is used to generate feature images from individual wavelet subbands, and a local energy function is computed corresponding to each pixel of the feature images. This feature vector is first used for training and later on for testing the SVM classifier. The experimental setup consists of images from the Brodatz and MIT VisTeX texture databases and a combination of some images therein. The proposed method produces promising classification results for both single and multiple class texture analysis problems.

AB - We present a novel texture classification algorithm using 2-0 discrete wavelet transform (DWT) and support vector machines (SVM). The DWT is used to generate feature images from individual wavelet subbands, and a local energy function is computed corresponding to each pixel of the feature images. This feature vector is first used for training and later on for testing the SVM classifier. The experimental setup consists of images from the Brodatz and MIT VisTeX texture databases and a combination of some images therein. The proposed method produces promising classification results for both single and multiple class texture analysis problems.

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T2 - 8th International Multitopic Conference, INMIC 2004

Y2 - 24 December 2004 through 26 December 2004

ER -

Wavelets and support vector machines for texture classification

Abstract

Publication series

Conference

Bibliographical note

ASJC Scopus subject areas

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Cite this