Computer Vision-Based Aluminum Scrap Grade Classification and Detection for Upcycling
摘要
The mechanical properties of aluminum alloys vary significantly across different grades due to differences in their chemical compositions. Therefore, when aluminium scraps are properly sorted during recycling, they can be more easily returned to their specific applications and yield a considerably higher value compared to unsorted scraps. Using computer vision for aluminum scrap sorting could potentially enhance the efficiency of the recycling process. In this work, we test and verify whether computer vision-based methods can be successfully deployed for commercial aluminum scrap grade classification using images only, on both the pre-shredding and post-shredding scraps. Image datasets of both pre-shredding and post-shredding scraps are carefully curated. The experimental results and the feature analysis show that the computer vision-based methods can classify the post-shredding scraps with high accuracy (