Novel approaches for detecting fabric fault using Artificial Neural Network with K-fold validation

Ahmed Shayer Andalib; Asif Salekin; Mohammad Raihanul Islam; Md Abdulla-Al-Shami

doi:10.1109/ICCITechn.2012.6509767

Novel approaches for detecting fabric fault using Artificial Neural Network with K-fold validation

Ahmed Shayer Andalib, Asif Salekin, Mohammad Raihanul Islam, Md Abdulla-Al-Shami

Research output: Chapter in Book/Entry/Poem › Conference contribution

3 Scopus citations

Abstract

In this paper we have proposed a novel method to detect the defects in woven fabric based on the abrupt changes in the intensity of fabric image due to the defects and have constructed a classification model to properly identify the defects. We have also improved an existing method based on histogram processing for the classifier. In classification model we have implemented Artificial Neural Network (ANN). Both of our newly proposed method and improved technique have outperformed the existing methods. We have implemented K-validation to estimate the performance of our classification model. Additionally we have analyzed the performance of our classification model for different experimental parameters. Finally we have presented a comparative analysis of these techniques.

Original language	English (US)
Title of host publication	Proceeding of the 15th International Conference on Computer and Information Technology, ICCIT 2012
Pages	55-60
Number of pages	6
DOIs	https://doi.org/10.1109/ICCITechn.2012.6509767
State	Published - 2012
Externally published	Yes
Event	15th International Conference on Computer and Information Technology, ICCIT 2012 - Chittagong, Bangladesh Duration: Dec 22 2012 → Dec 24 2012

Publication series

Name	Proceeding of the 15th International Conference on Computer and Information Technology, ICCIT 2012

Conference

Conference	15th International Conference on Computer and Information Technology, ICCIT 2012
Country/Territory	Bangladesh
City	Chittagong
Period	12/22/12 → 12/24/12

Keywords

Adaptive Median Filter
Artificial Neural Network
K-Validation
Roberts Operator

ASJC Scopus subject areas

Computer Networks and Communications
Information Systems

Access to Document

10.1109/ICCITechn.2012.6509767

Cite this

Andalib, A. S., Salekin, A., Islam, M. R., & Abdulla-Al-Shami, M. (2012). Novel approaches for detecting fabric fault using Artificial Neural Network with K-fold validation. In Proceeding of the 15th International Conference on Computer and Information Technology, ICCIT 2012 (pp. 55-60). Article 6509767 (Proceeding of the 15th International Conference on Computer and Information Technology, ICCIT 2012). https://doi.org/10.1109/ICCITechn.2012.6509767

Novel approaches for detecting fabric fault using Artificial Neural Network with K-fold validation. / Andalib, Ahmed Shayer; Salekin, Asif; Islam, Mohammad Raihanul et al.
Proceeding of the 15th International Conference on Computer and Information Technology, ICCIT 2012. 2012. p. 55-60 6509767 (Proceeding of the 15th International Conference on Computer and Information Technology, ICCIT 2012).

Research output: Chapter in Book/Entry/Poem › Conference contribution

Andalib, AS, Salekin, A, Islam, MR & Abdulla-Al-Shami, M 2012, Novel approaches for detecting fabric fault using Artificial Neural Network with K-fold validation. in Proceeding of the 15th International Conference on Computer and Information Technology, ICCIT 2012., 6509767, Proceeding of the 15th International Conference on Computer and Information Technology, ICCIT 2012, pp. 55-60, 15th International Conference on Computer and Information Technology, ICCIT 2012, Chittagong, Bangladesh, 12/22/12. https://doi.org/10.1109/ICCITechn.2012.6509767

Andalib AS, Salekin A, Islam MR, Abdulla-Al-Shami M. Novel approaches for detecting fabric fault using Artificial Neural Network with K-fold validation. In Proceeding of the 15th International Conference on Computer and Information Technology, ICCIT 2012. 2012. p. 55-60. 6509767. (Proceeding of the 15th International Conference on Computer and Information Technology, ICCIT 2012). doi: 10.1109/ICCITechn.2012.6509767

Andalib, Ahmed Shayer ; Salekin, Asif ; Islam, Mohammad Raihanul et al. / Novel approaches for detecting fabric fault using Artificial Neural Network with K-fold validation. Proceeding of the 15th International Conference on Computer and Information Technology, ICCIT 2012. 2012. pp. 55-60 (Proceeding of the 15th International Conference on Computer and Information Technology, ICCIT 2012).

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title = "Novel approaches for detecting fabric fault using Artificial Neural Network with K-fold validation",

abstract = "In this paper we have proposed a novel method to detect the defects in woven fabric based on the abrupt changes in the intensity of fabric image due to the defects and have constructed a classification model to properly identify the defects. We have also improved an existing method based on histogram processing for the classifier. In classification model we have implemented Artificial Neural Network (ANN). Both of our newly proposed method and improved technique have outperformed the existing methods. We have implemented K-validation to estimate the performance of our classification model. Additionally we have analyzed the performance of our classification model for different experimental parameters. Finally we have presented a comparative analysis of these techniques.",

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AB - In this paper we have proposed a novel method to detect the defects in woven fabric based on the abrupt changes in the intensity of fabric image due to the defects and have constructed a classification model to properly identify the defects. We have also improved an existing method based on histogram processing for the classifier. In classification model we have implemented Artificial Neural Network (ANN). Both of our newly proposed method and improved technique have outperformed the existing methods. We have implemented K-validation to estimate the performance of our classification model. Additionally we have analyzed the performance of our classification model for different experimental parameters. Finally we have presented a comparative analysis of these techniques.

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KW - K-Validation

KW - Roberts Operator

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Novel approaches for detecting fabric fault using Artificial Neural Network with K-fold validation

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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