کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
295102 | 511525 | 2014 | 8 صفحه PDF | دانلود رایگان |
• Nobody has detected crack defects from dark color and low contrast magnetic tiles.
• An automatic detecting mechanism for crack defects on magnetic tiles is proposed.
• Threshold of the curvelet reconstructed coefficients can be determined by GLCM.
• Curvelet is used to reconstruct images in order to reduce the effects of texture.
• The smallest crack length that can be detected is 0.8 mm and can meet factory request.
A new approach is proposed for automatically detecting crack defects with dark colors and low contrasts in magnetic tile images using the fast discrete curvelet transform (FDCT) and texture analysis. In this methodology the original images were first decomposed and reconstructed based on the FDCT. Then the thresholds of decomposition coefficients were calculated by texture feature measurements. With these thresholds the surface textures in the images can be eliminated. Finally by extracting contours from the reconstructed images, the expected images without textures but with crack defects contours were obtained. Experimental results show that the proposed method could eliminate the contours of the textures, and extract from the image cracks longer than 0.8 mm.
Journal: NDT & E International - Volume 62, March 2014, Pages 6–13