All Case Studies

Case Study

OCR and Scanned Document Processing

Python · FastAPI · OCR · Computer Vision · Document Processing

Executive Summary

Explored how to extract readable text from scanned or image-based documents while balancing accuracy, speed, and resource usage.

The Problem

Scanned PDFs are not searchable by default.
Low-quality images can reduce OCR accuracy.
Document processing had to balance speed, quality, and resource usage.

Architecture & Approach

1
Image preprocessing before OCR
2
OCR pipeline designed for scanned and mixed-content documents
3
FastAPI-based service layer for document extraction workflows
4
Post-processing to make extracted text more usable

Challenges & Trade-offs

Handling poor scan quality and mixed image/text content

Keeping inference and preprocessing efficient enough for real workloads

Outcomes & Results

A path toward searchable scanned documents
A more practical OCR workflow for document-heavy use cases