QR code localization using deep neural networks

Usage of computer-readable visual codes became common in our everyday life at industrial environments and private use. The reading process of visual codes consists of two steps, localization and data decoding. This paper introduces a new method for QR code localization using conventional and deep rectifier neural networks. The structure of the neural networks, regularization, and training parameters, like input vector properties, amount of overlapping at samples, and effect of different block sizes are evaluated and discussed. Results are compared to localization algorithms of the literature.