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@article{181439,
        author = {Pranay Pushkar},
        title = {A Hybrid Computer Vision Approach for Automated Parsing of Piping and Instrumentation Diagrams},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {4567-4571},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=181439},
        abstract = {The manual interpretation of Piping and Instrumentation Diagrams (P&IDs) in the process industry is a time-consuming, labor-intensive, and error-prone task. This paper presents a hybrid computer vision approach for the automated parsing and digitization of P&IDs. Our method integrates two robust techniques: template matching for symbol recognition and the Probabilistic Hough Transform for pipeline detection. By first identifying and locating standardized symbols with high accuracy, the system subsequently isolates and extracts the interconnecting pipelines. This two-stage process significantly reduces the complexity of line detection by eliminating symbols as sources of noise. The system is designed to process high-resolution binarized P&ID images, converting the graphical information into a structured data format representing equipment and their connections. Experimental results on a set of standard P&ID diagrams demonstrate the efficacy and accuracy of the proposed method, paving the way for automated P&ID analysis, verification, and integration with digital twin systems.},
        keywords = {Computer Vision, Hough Transform, P&ID Parsing, Process Engineering, Template Matching.},
        month = {June},
        }