Bispectrum for welds defects detection from radiographic images

Abstract

This paper presents a proposed method for the detection of welds defects from radiographic images. Firstly, the radiographic images were enhanced using Adaptive Histogram Equalization and were filtered using Mean and Wiener filters. Secondly, the welding area was selected from the radiography image. Thirdly, the images were converted to signals then the features were extracted from the Bispectrum of these signals. Finally, neural networks were used for training and testing the proposed method. The proposed model was tested on 100 radiography images in the presence of noise and image blurring. Results show that the proposed model yields best results for the detection of weld defects in radiography images when using the Bispectrum method estimated by Autoregressive moving average (ARMA) method.