A Set of Geometric Features for Neural Network-Based Textile Defect Classification

Joint Authors

Habib, Md. Tarek
Rokonuzzaman, M.

Source

ISRN Artificial Intelligence

Issue

Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-16, 16 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2012-02-07

Country of Publication

Egypt

No. of Pages

16

Main Subjects

Mathematics

Abstract EN

A significant attention of researchers has been drawn by automated textile inspection systems in order to replace manual inspection, which is time consuming and not accurate enough.

Automated textile inspection systems mainly involve two challenging problems, one of which is defect classification.

The amount of research done to solve the defect classification problem is inadequate.

Scene analysis and feature selection play a very important role in the classification process.

Inadequate scene analysis results in an inappropriate set of features.

Selection of an inappropriate feature set increases the complexities of the subsequent steps and makes the classification task harder.

By taking into account this observation, we present a possibly appropriate set of geometric features in order to address the problem of neural network-based textile defect classification.

We justify the features from the point of view of discriminatory quality and feature extraction difficulty.

We conduct some experiments in order to show the utility of the features.

Our proposed feature set has obtained classification accuracy of more than 98%, which appears to be better than reported results to date.

American Psychological Association (APA)

Habib, Md. Tarek& Rokonuzzaman, M.. 2012. A Set of Geometric Features for Neural Network-Based Textile Defect Classification. ISRN Artificial Intelligence،Vol. 2012, no. 2012, pp.1-16.
https://search.emarefa.net/detail/BIM-487679

Modern Language Association (MLA)

Habib, Md. Tarek& Rokonuzzaman, M.. A Set of Geometric Features for Neural Network-Based Textile Defect Classification. ISRN Artificial Intelligence No. 2012 (2012), pp.1-16.
https://search.emarefa.net/detail/BIM-487679

American Medical Association (AMA)

Habib, Md. Tarek& Rokonuzzaman, M.. A Set of Geometric Features for Neural Network-Based Textile Defect Classification. ISRN Artificial Intelligence. 2012. Vol. 2012, no. 2012, pp.1-16.
https://search.emarefa.net/detail/BIM-487679

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-487679