IMMEDIATE BUSINESS CARD INFORMATION EXTRACTION

1st P.RAJAPANDIAN, 2nd  V.ANIRUDHANE, 3rd  V.MADHIVANAN

1Associate Professor, Department of computer Applications, Sri Manakula Vinayagar Engineering College (Autonomous), Puducherry 605008, India rajapandian.mca@smvec.ac.in

2Post Graduate student, Department of computer Applications, Sri Manakula Vinayagar Engineering College (Autonomous),   Puducherry 605008, India  aanirudhane@gmail.com

3Post Graduate student, Department of computer Applications, Sri Manakula Vinayagar Engineering College (Autonomous),   Puducherry 605008, India  madhi2512@gmail.com

*Corresponding author’s email address: aanirudhane@gmail.com

ABSTRACT

Business card information extraction has emerged as a significant application of Optical Character Recognition (OCR), driven by advancements in deep learning and computer vision. This journal documents a Python-based approach leveraging Streamlit for a user-friendly interface and advanced OCR models, such as Tesseract, integrated with preprocessing techniques. The proposed system efficiently extracts textual information from business card images and organizes it into structured data formats, such as JSON or CSV. Unlike conventional OCR projects, this system incorporates enhancements like adaptive image augmentation, domain-specific fine-tuning, and real-time validation mechanisms. Furthermore, the project emphasizes scalability and usability by integrating with cloud storage and external APIs for streamlined data management. Comparative analysis demonstrates that our approach achieves superior accuracy and robustness across diverse business card layouts and environmental conditions.

KEYWORDS: OCR, Business Card Information Extraction, Tesseract, Deep Learning, Image Preprocessing, Streamlit, Data Structuring, Cloud Integration, API Interfacing.