What is OCR (Optical Character Recognition)?

What Is OCR?

OCR (Optical Character Recognition) converts text inside images, scanned documents, or PDFs into characters that software can process. The goal is to turn a visual invoice, form, or ID document into searchable text and structured data fields.

OCR is not just “reading letters”. A reliable pipeline combines image cleanup, page orientation correction, text region detection, character recognition, and output validation.

How OCR Works

1. Preprocessing: Noise reduction, contrast improvement, skew correction
2. Layout analysis: Separating paragraphs, tables, signatures, and fields
3. Character recognition: Sending printed or handwritten characters to a model
4. Post-processing: Reducing errors with language models, dictionaries, or business rules
5. Structuring: Extracting fields such as invoice number, date, and amount

Tesseract, ABBYY, Google Document AI, AWS Textract, and Azure AI Document Intelligence offer different tradeoffs in accuracy, cost, and integration depth. OCR is a practical business use case within computer vision.

Business Use

OCR is used to read incoming invoices, parse shipping labels, make old archives searchable, check bank receipts, and transfer form data into business systems. It can still misread characters, so critical workflows need confidence scores, human review, and field-level validation.

In RPA workflows, OCR is often the bridge between visual or PDF-based data and ERP, CRM, or accounting systems.