# 🧠 Intelligent OCR System for Scanned PDF Documents

**Master’s Thesis – Software Development Project**  
**Línea de trabajo:** Percepción computacional & Aprendizaje automático  
**Author:** Sergio Jiménez   
**Institution:** [UNIR - Universidad Internacional de La Rioja](https://www.unir.net/ingenieria/master-inteligencia-artificial/)

**Date:** 2025  

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## 📘 Overview

This project develops an **intelligent system for text extraction from scanned PDF documents**, combining **computer vision techniques** and **modern OCR models based on deep learning**.  
The goal is to overcome the limitations of traditional OCR tools (e.g., Tesseract) when dealing with **low-quality, skewed, or noisy scanned documents**, particularly in **Spanish**.

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## 🎯 Objectives

- Develop a **modular OCR pipeline** that processes scanned PDFs end-to-end.
- Compare classical OCR tools with **state-of-the-art deep learning approaches** (EasyOCR, TrOCR, CRNN).
- Evaluate performance using **Character Error Rate (CER)** and **Word Error Rate (WER)**.
- Provide a **CLI-based demonstration tool** and analysis module for automated evaluation.

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## 🧩 System Architecture

TODO