About Transcript Extractor
Advanced Academic Transcript Processing for Transfer Credit Evaluation
The system was developed to address the challenges faced by academic advisors and registrars in manually processing transfer credit evaluations, reducing processing time from hours to minutes while maintaining high accuracy through advanced OCR technology and intelligent pattern recognition.
Under Construction
Multi-engine OCR with consensus scoring, image preprocessing, and institution-specific watermark removal for maximum accuracy.
Configurable templates for Ivy Tech, Indiana University campuses, and Trine University with institution-specific extraction patterns.
Automated matching against comprehensive equivalency databases with grade-based filtering and transfer credit evaluation.
Comprehensive Excel reports with auto-adjusted column widths, multiple sheets, and detailed course analysis summaries.
Under Construction
Direct integration with Ellucian Ethos EEDM for seamless data transfer and staging CSV generation for student information systems.
Flexible template system allowing easy addition of new institutions and customization of extraction patterns without code changes.
Modern, fast web framework for building APIs with automatic documentation and type hints.
Data processing and Excel file manipulation for course equivalency analysis and reporting.
PDF processing library for text extraction, page rendering, and thumbnail generation.
Tesseract, PaddleOCR, and EasyOCR for multi-engine text recognition with consensus scoring.
Server-side templating engine for dynamic HTML generation and template inheritance.
Responsive CSS framework for modern, mobile-friendly user interface design.
Client-side interactivity for file uploads, dynamic UI updates, and user experience enhancements.
Production web server with reverse proxy configuration for scalable deployment.
Jeff Osborne
with Cursor
Documentation: Coming soon - comprehensive guides and API documentation will be available.
For Support contact Jeff Osborne: jposborne@manchester.edu