🔍 Project Overview
This project aimed to automate the extraction of information from scanned signature sheets, converting them into a structured CSV format for later use and analysis. It was part of a larger initiative to evaluate public support based on signature collections across Arkansas.
🧰 Tools & Technologies
- Python
- Azure Document Intelligence (OCR)
- Pandas / EDA
- Machine Learning for Signature Validation
🎯 Project Goal
Convert a large batch of scanned signature sheets into a tabular CSV format, enabling easy analysis and aggregation of names, addresses, counties, and signature dates.
📈 Outcome
The project was completed in-part. While the extraction of printed text (e.g., names, addresses, and counties) was successful, handwritten signatures proved to be a challenge due to OCR limitations. Future improvements include integrating handwriting recognition models or a human-in-the-loop validation workflow.
🖼️ Screenshots / Visuals
Example output, CSV snippet, or dashboard coming soon.