One-dimensional-based automatic defect inspection of multiple patterned TFT-LCD panels using Fourier image reconstruction

Abstract

Thin film transistor-liquid crystal display (TFT-LCD) has been used in a wide range of electronic devices. For large-sized and high-density TFT-LCD panel inspection, a high-resolution line scan is demanded. A TFT-LCD panel image at a fine resolution presents very complicated patterns with less regularity. The paper proposes a non-referential defect detection scheme that directly works on the one-dimensional (1D) line images using the Fourier image reconstruction. The 1D grey-level line image is first divided into small segments, each of the length of the repeated period for a given TFT-LCD panel. The divided segments are then combined as a two-dimensional (2D) image. The frequency components corresponding to the 1D background pattern can be easily identified in the 2D Fourier spectrum. By eliminating the frequency components in the 2D Fourier spectrum that represent the periodic structural pattern of the combined 2D image and then back-transforming the image using the inverse Fourier transform, the 2D Fourier reconstruction process can effectively remove the complicated background pattern and well preserve local anomalies. Experimental results on a number of micro-defects embedded in different patterned regions of TFT-LCD panels show that the proposed method can reliably detect various ill-defined defects.