Automatic defect inspection for LCDs using singular value decomposition

Thin film transistor liquid crystal displays (TFT-LCDs) have become increasingly popular and dominant as display devices. Surface defects on TFT panels not only cause visual failure, but result in electrical failure and loss of LCD operational functionally. In this paper, we propose a global approach for automatic visual inspection of micro defects on TFT panel surfaces. Since the geometrical structure of a TFT panel surface involves repetitive horizontal and vertical elements, it can be classified as a structural texture in the image. The proposed method does not rely on local features of textures. It is based on a global image reconstruction scheme using the singular value decomposition (SVD). Taking the image as a matrix of pixels, the singular values on the decomposed diagonal matrix represent different degrees of detail in the textured image. By selecting the proper singular values that represent the background texture of the surface and reconstructing the matrix without the selected singular values, we can eliminate periodical, repetitive patterns of the textured image, and preserve the anomalies in the restored image. In the experiments, we have evaluated a variety of micro defects including pinholes, scratches, particles and fingerprints on TFT panel surfaces, and the result reveals that the proposed method is effective for LCD defect inspections.