An Improved Anti-counterfeiting Printed QR Watermarking Algorithm Based on Self-Adaptive Genetic Algorithm

Abstract

To solve watermarking parameters optimization problem and enhance anti-counterfeiting performance, a self-adaptive genetic algorithm is proposed and introduced to improve robust QR code watermarking scheme. In the improved scheme, we adaptively change the genetic algorithm procedure according to the relation between the maximum fitness value and the average fitness value of a population. With the improved genetic algorithm procedure, it is easier to get better diveisity. In addition, mutation probability as well as crossover probability is adaptively modified to quickly seek out the optimal watermarking parameters. The tests indicate that the decoding rate of QR code noticeably increases without degrading detecting rate of digital watermark with the improved anti-counterfeiting printed QR code watermarking scheme.