An Image Processing Pipeline for Automated Packaging Structure Recognition
This addresses the need to reduce manual efforts in logistics supply chains, but appears incremental as it builds on existing computer vision techniques.
The paper tackles the problem of automating packaging structure recognition in logistics using computer vision, proposing a cognitive system that processes single RGB images and evaluating it on real-world data.
Dispatching and receiving logistics goods, as well as transportation itself, involve a high amount of manual efforts. The transported goods, including their packaging and labeling, need to be double-checked, verified or recognized at many supply chain network points. These processes hold automation potentials, which we aim to exploit using computer vision techniques. More precisely, we propose a cognitive system for the fully automated recognition of packaging structures for standardized logistics shipments based on single RGB images. Our contribution contains descriptions of a suitable system design and its evaluation on relevant real-world data. Further, we discuss our algorithmic choices.