caa a22 4500 606173064 CHVBK 20210128100731.0 cr unu---uuuuu 210128e20151201xx s 000 0 eng 10.1007/s10921-015-0305-9 doi (NATIONALLICENCE)springer-10.1007/s10921-015-0305-9 Classification of Welding Flaws in Gamma Radiography Images Based on Multi-scale Wavelet Packet Feature Extraction Using Support Vector Machine [Elektronische Daten] [Mohamed El-Tokhy, Imbaby Mahmoud] This paper has introduced a digital process aimed at automatically identify and classify flaws in the weld joints. Therefore, various algorithms are presented for computer aided detection (CAD) and classification. These algorithms include preprocessing algorithms using Gaussian pyramidal transform, contrast enhancement algorithm using contrast stretch and normalization method, noise reduction algorithm by blind image separation (BIS), measurement of the noise separation quality and image segmentation algorithm based on expectation-maximization (EM) method. Also, an algorithm for detection and classification of welding defects from radiographic images is presented. This algorithm is based on multi-scale wavelet packet (MWP) technique for feature extraction. Also, extraction of features from its transform domains is proposed to assist in achieving a higher classification rate. Moreover, the support vector machine (SVM) is applied for matching the extracted features. Consequently, classification error was computed for both normal and defect images. The obtained results confirm that much higher classification error was computed for defect image due to various objects may be in the image. Moreover, the accuracy of the considered algorithms is determined by statistical measurements. These algorithms have the potential for further improvement because of their simplicity and encouraging results. Therefore, it will motivate real-time flaws detection and classification for many CAD applications. Springer Science+Business Media New York, 2015 Image processing nationallicence Support vector machine nationallicence Classification nationallicence Transform domains nationallicence Gamma radiography nationallicence El-Tokhy Mohamed Engineering Department, NRC, Atomic Energy Authority, P. No. 13759, Inshas, Egypt aut Mahmoud Imbaby Engineering Department, NRC, Atomic Energy Authority, P. No. 13759, Inshas, Egypt aut Journal of Nondestructive Evaluation Springer US; http://www.springer-ny.com 34/4(2015-12-01), 1-17 0195-9298 34:4<1 2015 34 10921 https://doi.org/10.1007/s10921-015-0305-9 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10921-015-0305-9 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- El-Tokhy Mohamed Engineering Department, NRC, Atomic Energy Authority, P. No. 13759, Inshas, Egypt aut NATIONALLICENCE 700 1- Mahmoud Imbaby Engineering Department, NRC, Atomic Energy Authority, P. No. 13759, Inshas, Egypt aut NATIONALLICENCE 773 0- Journal of Nondestructive Evaluation Springer US; http://www.springer-ny.com 34/4(2015-12-01), 1-17 0195-9298 34:4<1 2015 34 10921