A Decoding Method for Distorted Two-dimensional Barcodes Using Auxility Line Detection by Convolution Neural Network

Abstract

Two-dimensional (2D) codes are widely used for various fields such as production, logistics, and marketing thanks to their larger capacity than one- dimensional barcodes. However, they are subject to distortion when printed on non-rigid materials, such as papers and clothes. Although general 2D code decorders correct uniform distortion such as perspective distortion, it is difficult to correct non-uniform and irregular distortion of the 2D code itself. This paper proposes a 2D code involving monochrome auxiliary lines that is robust against non-uniform, local distortion and its decode method that uses Convolution Neural Network for detection of auxiliary lines.