Optical Character Recognition (OCR)
Summary Definition: A technology that scans documents, PDFs, and images to convert printed or handwritten text into machine-readable and searchable data.
What is Optical Character Recognition?
Optical character recognition (OCR) is a type of character-reader technology that converts text from images and scanned documents into machine-readable data.
Instead of preserving content as a static image, character recognition technology analyzes and converts it into editable, searchable text. Thus, with OCR software and services, organizations can transform analog and visual materials into digital content for business use.
Key Takeaways
- Optical character recognition (OCR) refers to the process of identifying printed or handwritten text in scanned documents and images, and converting it into machine-readable text.
- OCR technology relies on a structured workflow that includes image preparation, character analysis, and text recognition to interpret visual content accurately.
- By converting written or printed content into structured, digital data, OCR systems help organizations reduce manual data entry, improve information accessibility, and support more efficient digital workflows across business environments.
How Does OCR Work?
Optical character recognition uses a series of structured steps to transform visual text into digital data.
- Image capture: Optical recognition software creates an OCR scan of the source material to capture all visible text.
- Image enhancement: The OCR software then improves the image by correcting alignment, adjusting contrast, removing background noise, and sharpening text to increase recognition accuracy.
- Character detection and recognition: The OCR reader analyzes shapes and patterns to identify individual letters, numbers, and symbols. More advanced optical recognition can also apply language models and contextual rules to interpret entire words.
- Text extraction: Based on the recognized characters, the optical character reader generates machine-readable text, which is made available for integration into other business systems.
What are the different types of OCR?
There are several types of optical character recognition, each designed to handle different kinds of text and document formats:
| Character Recognition Type | OCR Capability | Examples |
| Simple OCR (Standard OCR) | Identifies printed text in scanned documents or images and converts it into machine-readable text. | Extracting notes typed on a typewriter |
| Intelligent Character Recognition (ICR) | Applies intelligent word recognition and machine learning to recognize stylized text with improving accuracy over time. | Creating text from an old newspaper or magazine article |
| Optical Mark Recognition (OMR) | Detects and generates markable fields (e.g., checkboxes or selection bubbles) for forms. | Converting a PDF form into a Word document version |
| Handwritten Text Recognition (HTR) | Focuses on recognizing free-form handwriting, such as unique signatures. | Capturing cursive, historical handwriting or signatures |
| Zonal OCR | Extracts OCR data from predefined zones on a document, streamlining mass or expedited scanning. | Pulling content from portions of college applications |
What are Some Common Optical Character Use Cases?
An optical character recognition program can support a wide range of business and IT workflows, such as:
- Digitizing archival documents: OCR scanning converts physical files into searchable digital records, making documents easier to store, manage, and retrieve within document management systems.
- Automating data input: An OCR system extracts information from forms, invoices, and receipts and inputs it directly into business applications, reducing manual data entry.
- Supporting recordkeeping: OCR tools help standardize captured data for compliance regulations or internal audits and reports.
What are the Benefits of Optical Character Recognition for Businesses?
An optical character scanner allows businesses to manage information more efficiently by replacing manual, paper-based tasks with automated data capture. This, in turn, helps reduce administrative effort and limit errors.
In payroll, for example, OCR software captures key details from timecards, tax forms, or direct deposit authorizations, helping ensure accurate data flows into payroll systems without delays.
Likewise, procurement teams can use an OCR scanner app to quickly populate and file expense reports based on printed invoices or receipts. This streamlining helps expedite reimbursements while maintaining a clear, accessible audit trail.
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