A Recognition Method of Ceramic Microcosmic Images Based on SURF and Blockchain

Abstract

Ceramics have gradually occupied a more significant proportion in the art market and daily life in recent years. Therefore, the identification and anti-counterfeiting of ceramics have become more important with the continuous improvement of counterfeit ceramics. However, it is difficult for traditional ceramic identification and anti-counterfeiting technology to make instant, accurate and efficient identifications. Hence, based on the speed-ed up robust feature (SURF) algorithm, this paper proposes to take the microscopic surface features of ceramic images as the unique identifier for ceramic. In addition, blockchain was combined with distributed storage to ensure the security and reliability of these micro-characteristic data. At any time, ceramic images to be identified can be compared and verified with these images stored on the blockchain, and hence to determine the authenticity of the ceramics. Experimental results show that the proposed method has a high recognition rate and good robustness to problems. Compared with the traditional feature extraction methods, the efficiency and accuracy of proposed algorithm have been improved. The matching similarity rate between most imitations and genuine products using the proposed algorithm will not exceed 15%, thus accurately identifying imitations to achieve the anti-counterfeiting of ceramics.