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Defect detection in inhomogeneously textured sputtered surfaces using 3D Fourier image reconstruction

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Abstract

Texture analysis techniques have been used extensively for surface inspection, in which small defects that appear as local anomalies in textured surfaces must be detected. Traditional surface inspection methods are mainly concentrated on homogeneous textures. In this paper, we propose a 3D Fourier reconstruction scheme to tackle the problem of surface inspection on sputtered glass substrates that contain inhomogeneous textures. Such sputtered surfaces can be found in touch panels and liquid crystal displays (LCDs).

Since an inhomogeneously textured surface does not have repetition, self-similarity properties in the image, a sequence of faultless images along with the inspection image are used to construct a 3D image so that the periodic patterns of the surface can be observed in the additional frame-axis. Bandreject filtering is used to eliminate frequency components associated with faultless textures in the spatial domain image, and the 3D inverse Fourier transform is then carried out to reconstruct the image. The resulting image can effectively remove background textures and distinctly preserve anomalies. This converts the difficult defect detection in complicated inhomogeneous textures into a simple thresholding in nontextured images. Experimental results from a number of sputtered glass surfaces have shown the efficacy of the proposed 3D Fourier image reconstruction scheme.

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Correspondence to Du-Ming Tsai.

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Tsai, DM., Kuo, CC. Defect detection in inhomogeneously textured sputtered surfaces using 3D Fourier image reconstruction. Machine Vision and Applications 18, 383–400 (2007). https://doi.org/10.1007/s00138-007-0073-3

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  • DOI: https://doi.org/10.1007/s00138-007-0073-3

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