Color Texture Classification Using Adaptive Discrete Multiwavelets Transform

The classification of textures images has attracted the attention of many researchers. The multiscale techniques for gray level texture analysis have been intensively studied. In this paper, we aim on extending texture classification of color images by using the multiwavelets transform, a new notion...

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Main Author: Matheel Emad El-Deen Abdulmunim
Format: Article
Language:English
Published: Unviversity of Technology- Iraq 2012-02-01
Series:Engineering and Technology Journal
Subjects:
Online Access:https://etj.uotechnology.edu.iq/article_25916_6bf3ca7c2c53e9e61d8c57803b7e1819.pdf
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author Matheel Emad El-Deen Abdulmunim
author_facet Matheel Emad El-Deen Abdulmunim
author_sort Matheel Emad El-Deen Abdulmunim
collection DOAJ
description The classification of textures images has attracted the attention of many researchers. The multiscale techniques for gray level texture analysis have been intensively studied. In this paper, we aim on extending texture classification of color images by using the multiwavelets transform, a new notion addition to wavelet. The recognition of textures deals with both feature extraction and classification phases. In the classification phase the evolutionary computation techniques (genetic programming) was used for more speed recognition result evaluation. In our experiment results the proposed method has achieved 99.6% test accuracy on an average. In addition, the experimental results also show that classification rules generated by this approach are robust to some noises on textures
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spelling doaj.art-435498f240984ecfb9405022807de60d2024-02-04T17:38:39ZengUnviversity of Technology- IraqEngineering and Technology Journal1681-69002412-07582012-02-0130461562710.30684/etj.30.4.825916Color Texture Classification Using Adaptive Discrete Multiwavelets TransformMatheel Emad El-Deen AbdulmunimThe classification of textures images has attracted the attention of many researchers. The multiscale techniques for gray level texture analysis have been intensively studied. In this paper, we aim on extending texture classification of color images by using the multiwavelets transform, a new notion addition to wavelet. The recognition of textures deals with both feature extraction and classification phases. In the classification phase the evolutionary computation techniques (genetic programming) was used for more speed recognition result evaluation. In our experiment results the proposed method has achieved 99.6% test accuracy on an average. In addition, the experimental results also show that classification rules generated by this approach are robust to some noises on textureshttps://etj.uotechnology.edu.iq/article_25916_6bf3ca7c2c53e9e61d8c57803b7e1819.pdfclassificationmultiwaveletstextureand genetic programming
spellingShingle Matheel Emad El-Deen Abdulmunim
Color Texture Classification Using Adaptive Discrete Multiwavelets Transform
Engineering and Technology Journal
classification
multiwavelets
texture
and genetic programming
title Color Texture Classification Using Adaptive Discrete Multiwavelets Transform
title_full Color Texture Classification Using Adaptive Discrete Multiwavelets Transform
title_fullStr Color Texture Classification Using Adaptive Discrete Multiwavelets Transform
title_full_unstemmed Color Texture Classification Using Adaptive Discrete Multiwavelets Transform
title_short Color Texture Classification Using Adaptive Discrete Multiwavelets Transform
title_sort color texture classification using adaptive discrete multiwavelets transform
topic classification
multiwavelets
texture
and genetic programming
url https://etj.uotechnology.edu.iq/article_25916_6bf3ca7c2c53e9e61d8c57803b7e1819.pdf
work_keys_str_mv AT matheelemadeldeenabdulmunim colortextureclassificationusingadaptivediscretemultiwaveletstransform