Hand-drawn electrical circuit diagram graph generation

This study presents an automated approach for the generation of graphs from hand-drawn electrical circuit diagrams, aiming to streamline the digitization process and enhance the efficiency of traditional circuit design methods. Leveraging image processing, computer vision algorithms, and machine learning techniques, the system accurately identifies and extracts circuit components, capturing spatial relationships and diverse drawing styles. The resulting graph-based representation facilitates seamless integration with computer-aided design tools, enabling rapid validation and analysis of circuit designs. This automated approach holds promise for accelerating the design workflow, reducing manual transcription errors, and promoting collaborative efforts in both educational and professional contexts, ultimately contributing to advancements in the field of electrical circuit design.