Open AccessAn Improved Anti-counterfeiting Printed QR Watermarking Algorithm Based on Self-Adaptive Genetic Algorithm
Author(s) -
Rong Xie,
Pengcheng Huang
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/768/5/052002
Subject(s) - digital watermarking , crossover , watermark , algorithm , genetic algorithm , code (set theory) , scheme (mathematics) , decoding methods , computer science , encryption , image (mathematics) , mathematics , mathematical optimization , artificial intelligence , operating system , mathematical analysis , set (abstract data type) , programming language
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.