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@article{184201,
        author = {Prof.Santhosh SG and Sunith GP and Amtual Mateen Sultana},
        title = {Text Extraction and Classification from Real-Time Bilingual Road Signboards Using OCR Engines},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {4},
        pages = {548-559},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=184201},
        abstract = {The objective of the work is to develop a system that employs image processing methods to retrieve text from multilingual roadway directional signs. Multilingual signboards with language overlap, inconsistent fonts, and noisy real-time images complicate automated text extraction in various regions (English, Hindi, Kannada, etc.). This work includes efficient image preprocessing methods to improve the clarity of live images. Two OCR engines, EasyOCR and Tesseract, are employed to extract the entire text content, subsequently categorized into English and non-English groups. To enhance the evaluation of the system, a specialized performance metric module has been established. This module examines the speed and reliability of both OCR engines through processing time. Visual depictions like bar charts and line graphs have been incorporated to assess the engines' performance and determine the quicker and more dependable choice. The incorporation of this performance analysis offers a more thorough insight into the system’s functioning and practical relevance.},
        keywords = {EasyOCR, Image processing, MSER, Performance metric, Road signboards, Tesseract.},
        month = {September},
        }