What is optical character recognition?
Optical character recognition (OCR) extracts machine-readable text from images. Professionals use OCR to scan receipts, forms, and contracts, initially in an image format, into editable text documents of the same.
OCR software eliminates manual data entry and improves fraud detection, helping various departments, like human resources, accounting, or finance, to quickly glean information from paper and digital documents in mass quantities.
Organizations have workflows that depend on print media or paper documents such as legal contracts. Digitizing it helps, but it creates images that are tricky to edit. OCR technology solves this by converting text images into text data, facilitating editing and modifications with text editors.
Types of optical character recognition
Usage and applications form the base of OCR classifications. Data scientists categorize optical character recognition into the following types:
- Simple OCR software saves multiple text image patterns and fonts as templates. It compares text images to its internal databases to find a match. When the system matches it word by word, it’s known as optical word recognition. Since there are numerous fonts and writing styles, this solution has limitations.
- Intelligent character recognition (ICR) technology reads text the same as humans. It trains machines to analyze text over multiple levels and repeatedly process the image. Machine learning (ML) systems look for image attributes like lines, intersections, and loops and combine them to get the outcome.
- Intelligent word recognition processes whole word images instead of preprocessing characters in an image.
- Optical mark recognition recognizes logos, text symbols, and watermarks in paper documents.
Optical character recognition benefits
OCR makes it easy to manage unsearchable data. It saves time and resources businesses would have spent if they were to manage paper documents and text images manually. OCR offers several other benefits, including:
- Enhances accessibility: OCR makes text in images more searchable and editable. Businesses can search, view, edit, and repurpose image text data through OCR software.
- Improves data security: Digital data is a significant security concern. OCR adds a layer of security while processing and extracting text data. OCR accurately converts the paperwork while ensuring only authorized people can access it.
- Increases efficiency: OCR manages paper documents with a cost-effective approach. OCR helps organizations adopt paperless processes and use automated workflows to expedite operations. Teams can capture data, extract information, and validate faster than manually working from the same activities.
- Enables advanced actions: Teams can perform actions such as compressing into ZIP files, highlighting text, or attaching text data to emails.
- Reduces errors: Professionals can avoid human errors and inconsistencies with OCR technology, saving the business’ reputation and time spent on corrections later.
- Assists in decision making: OCR is often a part of artificial intelligence (AI) solutions, such as technology reading license plates, recognizing brand logos, and identifying packaging and advertising. Information like this helps businesses make better marketing and operational decisions.
How optical character recognition works
Optical character recognition works through the following steps.
These steps depend on an organization’s workflow and needs from the system.
- Acquires image: The scanner reads documents or text images and produces corresponding binary data. OCR differentiates light areas as background and dark areas as text.
- Pre-process: OCR cleans the images, eliminates errors, and prepares them for reading. It involves fixing alignment issues, removing spots, smoothing edges, and cleaning lines and boxes in an image.
- Recognizes text: The technology uses either pattern matching or feature extraction to recognize text. Pattern matching isolates the character image as a glyph and compares it with an internally stored glyph. Feature matching breaks glyphs down into lines, curves, and various image attributes to find the nearest neighbor among stored glyphs.
- Post-process: The system converts extracted text data into digital files. Some OCR systems create annotated portable document formats (PDF).
Optical character recognition applications
The majority of businesses use OCR now and then for administrative tasks. There are a few sectors that use it more intensively than others.
- Healthcare: OCR processes patient records and tests and assists in insurance payments. It streamlines workflows and reduces the manual work involved in keeping records current.
- Banking: Using OCR, financial institutions and banks verify paperwork, deposit checks, and other paper transactions. It prevents fraud and provides transaction security.
- Logistics: The transportation and logistics sector uses OCR to track invoices, receipts, shipment labels, and other documents for more efficiency. It eliminates manual entry, reducing the time and minimizing errors in the process.
Optical character recognition vs. intelligent document processing (IDP)
Both are two different text reading methods. OCR reads text and converts it into digital form through pattern or feature matching. On the other hand, IDP uses AI to read text and extract information.
Although IDP shows better accuracy than OCR, it’s a more time-consuming process.
Learn more about the history of OCR and explore the best OCR products on the market.