GLCM and ANN based Approach for Classification of Radiographics Weld Images

被引：0

作者：

Kumar, Jayendra ^{[1
]}

Srivastava, S. P. ^{[1
]}

Anand, R. S. ^{[1
]}

Arvind, Pratul ^{[2
]}

Bhardwaj, Shivain ^{[3
]}

Thakur, Ankit ^{[3
]}

机构：

[1] Indian Inst Technol Roorkee, Dept Elect Engn, Roorkee, Uttar Pradesh, India

[2] Dr Akhilesh Das Gupta Inst Technol & Management, Dept Elect & Elect Engn, New Delhi, India

[3] Dr Akhilesh Das Gupta Inst Technol & Management, Dept Mech Engn, New Delhi, India

来源：

2018 IEEE 13TH INTERNATIONAL CONFERENCE ON INDUSTRIAL AND INFORMATION SYSTEMS (IEEE ICIIS) | 2018年

关键词：

radiographic weld images; non - destructive inspection; GLOM; image classification; GLCM; artificial neural network; NDT SYSTEM; INSPECTION;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The process of welding involves welding defects. Welded material should be inspected accurately in order to ensure the quality of the design and operation. Non - Destructive Inspection is one of the important aspects which is responsible for identifying the flaw defect. An attempt has been made in the present work to accurately identify and classify the weld defects. A database of 79 images with 08 defects have been collected from Department of Mechanical and Industrial Engineering, Indian Institute of Technology Roorkee. The image database has been pre-processed and the features have been extracted by LLCM and feed to Artificial neural network for classification. Both 08 and 64 level features have been extracted by GLCM and fed to neural network. The features have been fed to both Feed Forward and Cascade Forward neural network for classification. Even though the quality of image database is not good, classification accuracy of 88.6% is obtained.

引用

页码：181 / 185

页数：5

共 21 条

[1]

[Anonymous], 2011, Can J Artif Intell, Mach Learn Pattern Recognit

[2]

[Anonymous], 2017, MATLAB

[3]

Arvind Pratul, 2012, 2012 IEEE Symposium on Computers & Informatics, P113, DOI 10.1109/ISCI.2012.6222677

[4]

Arvind Pratul, 2012, AM I PHYS C SERIES

[5]

Barai V., 2002, P NAT SEM NOND EV CH

[6]

Da Silva RR., 2007, MATER EVAL, V643, P1

[7] Multi-step radiographic image enhancement conforming to weld defect segmentation [J].

Dang, Changying ;

Gao, Jianmin ;

Wang, Zhao ;

Chen, Fumin ;

Xiao, Yulin .

IET IMAGE PROCESSING, 2015, 9 (11) :943-950

[8] A laser-EMAT system for ultrasonic weld inspection [J].

Dixon, S ;

Edwards, C ;

Palmer, SB .

ULTRASONICS, 1999, 37 (04) :273-281

[9]

Hongwei Liu, 2010, Proceedings 2010 Sixth International Conference on Natural Computation (ICNC 2010), P456, DOI 10.1109/ICNC.2010.5583151

[10]

Kumar J, 2014, INT CONF ADV ELECTR

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