Inspection of LCD light-guide plate using digital image processing is proposed. Binary dot-pattern images from SEM observation are obtained by image segmentation. Pattern recognition for the images is then performed using moment invariants, Bayes classifier, and Neural network. The rotation independent classification for the recognition using only one descript shape factor are also proposed to reduce storage space. It is found the method has been applied successfully in inspection of different defects on the plate subject to any rotation angles and image scales.