Ceramics appraisal is a hot topic in field of cultural relic collection. Traditionally, there are mainly two types of ceramics appraisal methods, which are experience-based and technology-based methods. In practice, both methods will cause high cost and time-consuming. A novel vision-based method, which is mainly inspired by the idea of biometrics recognition techniques, is proposed to achieve efficiently verification of the identity of a ceramics. In this method, the microscopic information of a ceramics captured by a digital microscope camera is used as the characteristics for verification. In technical detail, speeded up robust features(SURF) is first employed to align the probe image to the gallery images. Local binary patterns(LBP) features are then extracted from the two aligned images. Finally, Chi-square distance is calculated to measure the similarity between probe and gallery. Experiments on the dataset constructed by this paper demonstrate the state-of-the-art performance of proposed method.