P‐29: Noise reduction and defect detection algorithm in white‐light scanning interferometry for display panel inspection

Abstract

White‐light scanning interferometry (WSI) has been widely used for the inspection of various display panels by 3D surface imaging from the micrometer scale to the nanometer scale. However, WSI often fails to sense light reflected from towering defects due to diffused reflection, represented by near‐zero heights, called black spot (b‐spot). It is challenging to detect the b‐spot defect especially in display pad area with varying heights. In addition, vibration of WSI facility hinders a defect spot due to harsh noise amplification. To resolve the issues, we proposed a novel and efficient image processing algorithm which consists of five steps. The first step is image denoising by median filtering with rectangle kernels. The second is pad area preprocessing to avoid misdetection. The third is to identify the presence of b‐spot defect using curvature of 1D projection array of an image. The fourth is defect detection through minimum value finding method. The last is Laplace fitting to infer the height of towering b‐spot defect. We conducted an experimental study using WSI raw data of defective display panels to evaluate the defect detection rate and the reliability of inferred height. We also calculated the correlation between the inferred height by Laplace fitting and measured height by atomic force microscopy (AFM) as a gold standard. We have shown that the proposed method can effectively detect a towering b‐spot defect position with much improved detection rate and infer the height with high precision.