GLCM and ANN based Approach for Classification of Radiographics Weld Images
Autor: | Shivain Bhardwaj, Ankit Thakur, R. S. Anand, S.P. Srivastava, Pratul Arvind, Jayendra Kumar |
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Rok vydání: | 2018 |
Předmět: |
0209 industrial biotechnology
Artificial neural network Cascade forward neural network business.industry Computer science Feature extraction Feed forward Process (computing) Pattern recognition 02 engineering and technology Welding law.invention 020901 industrial engineering & automation Image database law 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business |
Zdroj: | ICIIS |
Popis: | 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 GLCM 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. |
Databáze: | OpenAIRE |
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