Texture analysis and classification

Type :

Term papers

Pages :

5 pages

Format :

.pdf

Published date :

10/09/2009

Category :

Science & technology

Sub category :

Computer science

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Summary :

Abstract
Introduction
Logical operators
1. Generation of higher order matrices
2. Logical hadamard operator
3. Arithmetic operator
4. Adding operator
5. Equivalence operator
6. Conjunction operator
7. Disjunction operator
Texture analysis and classification with logical operators
1. Texture analysis
Algorithm for texture classification
1. Feature extraction process
2. Normalization of features
3. Feature selection
4. Classification
Experimental results
1. Classification using brodatz textures
2. Comparison with the other methods
3. Effect of different classifiers and normalization techniques
Applications
Conclusions
References

Abstract

texture classification is an image processing technique by which different regions of an image are identified based on texture properties. This process plays an important role in industrial, biomedical and remote sensing applications. One of the major developments recently in texture segmentation has been the use of multi resolution and multi channel descriptions of the texture images. This description provides information about the image contained in ever smaller regions of the frequency domain, and thus provides a powerful tool for the discrimination of similar textures. The use of scale-space-filtering is equivalent to a decomposition of the image interims of wavelets. The logical operators considered here are order-2elementary matrices. The building blocks for defining these matrices are 0,1, -1, matrices of order 1X1. The matrices can be formed by defining the following operations on these basic building blocks. This process of generation of order-2 matrices and operations has been used.