[4Pin1] インタラクティブ(2)

[4Pin1-07] A Decoding Method for Distorted Two-dimensional Barcodes Using Auxility Line Detection by Convolution Neural Network

〇Kazuki Kuratsuwa¹, Makoto Kamizono¹, Hiroshi Kawasaki², Satoshi Ono¹ (1. Kagoshima University, 2. Kyushu University)

Keywords:Convolutional Neural Network, QR code, Image Restoration

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.