Robust Shipping Label Recognition and Validation for Logistics by Using Deep Neural Networks

Abstract

Shipping labels are widely used in logistics. It is important to ensure the quality of printing label and to verify contents of the shipping label on the package. We developed a verification and recognition method for various types of shipping labels by using deep neural networks. The experimental results showed 96% recognition accuracy in rotation-invariant conditions. Also, we introduce Google Maps API for validating the address which can reduce the cost of returning packages due to the invalid address. To train and evaluate the method, we have generated and collected 25 different types of shipping label dataset. We plan to release the dataset on our website1.