AI-assisted waste paper grade recognition – Recovered Paper Eye (RepEye)
Incoming inspection of baled paper for recycling reaches a new level: Using artificial intelligence (AI) methods, specifically machine learning, we have developed a camera-based inspection system that can determine the waste paper grade by analyzing the front of the bale directly on the truck bed. Using a permanently installed camera the entire load of a truck in terms of grade conformity and composition can be approximately evaluated. The basis for the AI’s learning process and thus for the reliability of detection is an extensive image data set of individual bales with a wide variety of qualities.
Measurement parameters:
- Recovered paper grades according to standard EN 643
- Proportions of brown and light components
Advantages and benefits:
- Comprehensive objective and complete visual inspection of incoming bale goods directly on the truck bed
- Real-time comparison of requested and current quality of recovered paper deliveries
- Detection of conspicuous individual bales
- System continuously learns on-site using additional context information
- Simple hardware installation