OCR-Based Card Field Extraction System
This project focuses on extracting structured information from card images using image processing, OCR, and regular expressions. The system processes images of ID cards, bank cards, and similar field-based cards, extracts visible text, and organizes the detected data into meaningful fields. It demonstrates how OCR can be used as a practical automation layer for document understanding and data entry workflows.
The Challenge
Many workflows still require manual data entry from cards and documents, which is slow, repetitive, and prone to human error. Extracting fields such as names, numbers, dates, or identifiers from images can save time and improve automation in form-filling and verification scenarios.
The Solution
The solution applies image preprocessing to improve OCR quality, extracts text from the card image, and uses regular expressions and field-matching logic to identify structured information. The extracted fields can then be used for automated form filling, validation, or storage in another system.
Architecture
The pipeline starts with an uploaded or selected card image. Image processing techniques are applied to clean and prepare the image for OCR. The OCR engine extracts raw text, then regex-based parsing identifies important fields such as names, card numbers, dates, and other structured values. The final output is organized into usable field data.