A discrete information coding matrix algorithm based on image features for tracking circulation of commodities

Abstract

For fast-consumed-commodities industry, it is usually difficult for producers to track the commodities in their circulation process, especially, when their labels have been damaged. In this paper, we develop a novel method based on channel coding theory of forward error correction (FEC) to prevent the flooding of counterfeit products with a very low cost and easy implementation. This anti-interference matrix information coding method has a strong ability to resist damage and high recovery rate, and can produce a large number of nonrepeated codes in terms of different characteristics of demand, yielding a great enhancement of anti-counterfeiting trace capacity. However, the process of reading information strongly relies on artificial means that requires a high cost and reduces the efficiency. For this reason, we propose an efficient approach for image feature extraction based on discrete information coding matrix. It takes the advantage of wearing perspective clipping method to obtain the revised image with printed matrix information and then extract the regions of interest (ROI) that carry the information about the coding matrix by working out its row and column coordinates with the center of gravity method. The matrix code recognition software is implemented. The simulation and experimental results show that the method is effective and robust. KEYWORDS FEC, image identification, Reed-Solomon codes, tracking circulation of commodityInt J Numer Model. 2019;32:e2597.wileyonlinelibrary.com/journal/jnm

Collaborative Music Creation Method Based on Image Collection of Lattice Code

“…Early electronic music was determined by the way it was created and the technical way it was presented on the broadcast or through the speakers in the theater. Wan et al proposed an image feature extraction method based on discrete information coding matrix [1]. Blackburn and Claridge considers generalization of matrix channels to model random linear network codes [2].…”