A discrete information coding matrix algorithm based on image features for tracking circulation of commodities. (16th April 2019)

• Record Type: Journal Article
• Authors: Wan, Guo Chun; Zhou, Fo Zhi; Gao, Chuang; Tang, Ling Yi; Tong, Mei Song
• Is Part Of: International journal of numerical modelling. Volume 32:Number 5(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-04-16
• Subjects: FEC -- image identification -- Reed‐Solomon codes -- tracking circulation of commodity; Electric networks -- Mathematical models -- Periodicals; Electronics -- Mathematical models -- Periodicals; 621.3011
• DOI: 10.1002/jnm.2597
• Languages: English
• ISSNs: 0894-3370

Abstract

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.