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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/17435
Title: Multi - Class welding flaws classification using texture feature for radiographic images
Authors: Kumar J.
Anand, Radhey Shyam
Srivastava S.P.
Published in: Proceedings of 2014 International Conference on Advances in Electrical Engineering, ICAEE 2014
Abstract: The paper presents a novel approach for multi-class weld flaw classification by means of Gray level co-occurrence matrix (GLCM) based texture feature extraction technique and Artificial Neural Network classifier. The weld radiography films have been digitized using CCD camera, followed by image processing techniques i.e. RGB to gray conversion, region of interest (ROI) selection, noise reduction and contrast enhancement. Subsequently a set of 8, 64 and 44 texture features vectors have been obtained from each of the digitized weld images by means of GLCM. Further, the features obtained have been classified with cascade-forward back propagation neural network. The proposed system has obtained overall classification accuracy of 86.10% for nine different types of weld flaws of digitized radiographic images. © 2014 IEEE.
Citation: Proceedings of 2014 International Conference on Advances in Electrical Engineering, ICAEE 2014, (2014). Vellore, Tamilnadu
URI: https://doi.org/10.1109/ICAEE.2014.6838443
http://repository.iitr.ac.in/handle/123456789/17435
Issue Date: 2014
Publisher: IEEE Computer Society
Keywords: GLCM
multi-class classification
neural network
radiographic images
texture feature
weld flaws
ISBN: 9.78148E+12
Author Scopus IDs: 57210529896
56363331000
7403307033
Author Affiliations: Kumar, J., Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee, India
Anand, R.S., Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee, India
Srivastava, S.P., Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee, India
Appears in Collections:Conference Publications [EE]

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