Publication
Instance Segmentation Based Graph Extraction for Handwritten Circuit Diagram Images
Johannes Bayer; Amit Kumar Roy; Andreas Dengel
In: International Conference on Pattern Recognition Applications and Methods. International Conference on Pattern Recognition Applications and Methods (ICPRAM-2023), 17th International Conference on Pattern Recognition Applications and Methods, located at International Conference on Pattern Recognition Applications and Methods, February 12-24, Lisbon, Portugal, SCITEPRESS, 2023.
Abstract
Handwritten circuit diagrams from educational scenarios or historic sources usually exist on analogue media. For deriving their functional principles or flaws automatically, they need to be digitized, extracting their electrical graph. Recently, the base technologies for automated pipelines facilitating this process shifted from computer vision to machine learning. This paper describes an approach for extracting both the electrical components (including their terminals and describing texts) as well their interconnections (including junctions and wire hops) by the means of instance segmentation and keypoint extraction. Consequently, the resulting graph extraction process consists of a simple two-step process of model inference and trivial geometric keypoint matching. The dataset itself, its preparation, model training and post-processing are described and publicly available.