In order to solve the problem of distinguishing the authenticity of Ji anzhan,an experimental prototype system is established through an improved scale-invariant feature re cognition algorithm to identify different types of the glaze of Jianzhan.The researched recognition mo del provides services on the cloud in order to judge the similarity of the glaze of Jianzhan.The system uses the Streamlit platform to build an experimental human-computer interaction interface.For the recognit ion model, an image preprocessing strategy is researched and developed based on the boundary following method,which aims to filter out the interference of background and irrelevant material characteristics,impr ove the recognition ability of images taken under natural conditions,and reduce the possibility of misjudgm ent of the glaze of Jianzhan.Using an improved support vector machine (SVM)-based scale invariant feature transform (SIFT) feature matching classification strategy,a number of performance experim ents are designed to obtain sufficient data set resolution,SVM optimal hyperparameters and initializ ation required minimum data set parameter model.Experiments have confirmed that the system can clearly distinguish the similarities of the same types of glaze patterns (rabbit hair glaze,oil drip gl aze).It uses a given limited data set to provide a recognition accuracy rate of up to 92.60% and increases th e single recognition speed by 0.84 s.