What Optical Character Recognition (OCR) Meaning, Applications & Example
A technology that recognizes and extracts text from digital images.
What is Optical Character Recognition (OCR)?
Optical Character Recognition (OCR) is a technology that converts different types of documents—such as scanned paper documents, PDFs, or images captured by a digital camera—into editable and searchable data. OCR uses machine learning and pattern recognition algorithms to identify and extract text from images, making it useful for digitizing printed documents and automating data entry.
How OCR Works
- Image Preprocessing: The image is cleaned and optimized by removing noise, correcting skew, and adjusting contrast to improve text recognition accuracy.
- Text Detection: The OCR system analyzes the image and locates areas containing text. This step involves segmenting the image into individual characters or words.
- Character Recognition: Using trained algorithms, the system identifies each character or word by comparing it to a set of pre-defined templates or by using machine learning models that have learned to recognize characters.
- Postprocessing: The recognized text is then processed to correct errors and improve accuracy, often using dictionary or language models.
Applications of OCR
- Document Digitization: OCR is widely used in libraries, archives, and offices to digitize printed documents and make them searchable, saving space and time.
- Invoice and Receipt Processing: In finance and accounting, OCR is used to extract information from invoices, receipts, and other business documents to automate data entry and improve efficiency.
- Text-to-Speech: OCR helps visually impaired individuals by converting printed text into digital format that can then be read aloud by text-to-speech software.
- License Plate Recognition: OCR is used in automatic number plate recognition systems in parking lots, toll booths, and security checkpoints.
Example of OCR
An example of OCR in action is document scanning. When a user scans a printed document using an OCR tool, the text is extracted and saved as a digital, editable file such as a Word document or PDF. This allows the user to search, edit, and store the document efficiently, turning a once-static paper document into a dynamic, accessible digital file.