What is OCR Software?
Optical character recognition (OCR) is text recognition software that transforms paper documents, photos, and videos into searchable digital document files. By processing a picture or document with OCR, businesses change it into machine-readable PDFs you can search, share, edit, and use for data analysis.
An OCR solution can generate searchable data from scanned documents, photos, videos, camera image files, and image-only PDFs. Using an OCR program eliminates the need to enter data manually, loading digitized information into a database for business intelligence, auditing, processing, compliance, or even as part of a larger Robotic Process Automation (RPA).
Several open-source and SaaS OCR tools are available, each allowing businesses to detect typed or handwritten language in images and transform them into searchable, machine-readable documents. Of the available options, Amazon Textract is the industry-leading standard for businesses that want a highly scalable, deep-learning technology to meet their needs. Textract goes beyond just OCR, identifying the contents of fields (like key-value pairs), the context of information, information within tables, and more.
Amazon Textract analyzes billions of videos and images daily, offering a comprehensive suite of intelligent document processing capabilities. The easy-to-use interface is perfect for those who don’t have machine learning software expertise, with intuitive API operations that allow you to analyze images and PDF files easily. Textract is always learning and improving, with Amazon continually adding new features to the service to ensure businesses can derive as much value as possible..
What are key features of OCR software?
There are several features that optical character recognition software includes that streamline business processes.
Extract text from forms.
Organisations should look for OCR software that can extract form data with context. Converting a form into a paragraph of text hides the data within the form and makes it less usable. Instead, the OCR software should convert forms into structured data formats that can be easily uploaded into data stores for analytics. Automatic data entry reduces the likelihood of human errors in the data entry process and expedites data digitization.
Amazon Textract uses AI models to automatically detect key-value pairs in documents and scanned forms. These key-value pairs, like ‘Name’ as the key and the person’s name as the value, can help give context to documents and support with data collection, processing, and sorting. Textract extracts data and transforms it into a structured JSON format so downstream business intelligence platforms can easily ingest and process the data.
Extract data from table cells
Tables are a standard method of presenting information in a structured format, especially in business invoices, tax documents, or other formal documents. Some OCR platforms struggle with understanding the format implied across the columns and rows of a table. Leading OCR tools can extract text from tables and table cells while preserving their structural relationships. An OCR engine supporting this feature is vital for any field that relies on tabular extracted text data.
Amazon Textract can extract data from tables and individual table cells, returning results as a TXT file, CSV, or JSON, depending on which is most appropriate for your business. Tables are returned as Block objects, able to distinguish between table titles and words that fall under specific column or row categories using a form of optical word recognition.
Automatically identify layouts
Businesses will likely have to interact with documents that vary across a wide range of formats, styles, and contents. For example, one company may have to process numerical invoices, ingest long written documents, interact with whitepapers, and look through contracts with signatures, names, and addresses. Understanding these different layouts and how information is structured is an essential feature of OCR engines.
Amazon Textract can detect and categorize key elements of different layouts, identifying tables, headers, footers, paragraphs, handwritten additions, titles, and signatures. By using bounding boxes, Amazon Textract can locate unique metadata for each element, with the searchable document mirroring the original layout.
Automatically detect signatures
Signatures are a regular feature of contracts, for verification purposes, and in compliance files. Businesses need the capability of rapidly detecting whether a document has the required signatures, without having to read through entire contracts manually. Optical character recognition software that can scan documents to identify signatures removes the need for manual contract review, expediting the process of verifying documents.
Amazon Textract instantly identifies handwritten marks on a page, using its analytical capabilities to identify cursive handwriting or other factors that help demonstrate a signature. Textract then signals to users where signatures are located within scanned legal documents, allowing them to skip directly to a particular area of the document and verify its presence. Businesses can use this process in combination with RPA to automatically request signatures if they are not found on a vital document.
Query-based extraction
To save time, businesses may want to directly query their digitized documents, instantly gaining access to answers to their questions. For example, instead of reading an entire document, they may query by searching for a certain date, name, or another specific piece of information. While traditional OCR engines only digitize documents, modern software solutions can also create a database for users to query.
For example, Amazon Textract can query specific information in the document. Users could type “What is the customer’s payment reference number?”, which then triggers Amazon Textract to search the document for this information and then return it to the user. Textract uses the AnalyzeDocument and GetDocumentAnalysis features in this process, allowing users to search for any information they would like in the document. Users can create custom queries by adapting the model output to their company’s documents. Adapting the model with additional annotations or labeling for specific use cases and business scenarios can help achieve a diverse range of query options.
Code-based extraction support
Code-based extraction support enables businesses to integrate OCR tools into backend systems, combining them with other tools like RPA workloads, GUI tools, and other backend systems. Integrating OCR through code helps to amplify the capabilities of OCR tools, with APIs that connect this software to other applications. Amazon Textract provides a range of APIs that businesses can use to further streamline business processes and automate larger internal procedures.
How does OCR extract text from forms?
If your organization has specific use cases for which you plan to use OCR, look for optical character recognition software customized to that use case. Some common use cases include:
Invoices and receipts
Invoices and receipts include heavily structured data, including billing figures, tax information, currency details, account numbers, and names. OCR engines like Amazon Textract can streamline the collection of this information, automating data collection and smoothing out financial-related billing and processes. By pairing OCR technology with other business software, companies can automate scanning invoices, initiating refunds, and reimbursing users for company-related purchases.
Identity documents
Using OCR engines to process identity documents is another common use case for businesses. Organizations that need to extract information from passports, driver’s licenses, citizenship cards, or other identity-based documents can use OCR engines to streamline onboarding, compliance, access control, and data collection. Integrating an OCR platform like Textract into your business can improve customer experiences while reducing strain on administrative staff, as they will no longer have to process image files manually.
Loan applications
The process for applying for a loan includes gathering numerous documents, ranging from bank statements, identity documents, years of tax returns, credit reports, letters from employers, and others, depending on the purpose of the loan. By using OCR technology to process these documents, businesses can save time and reduce the turnaround time for updating the progress of a loan application. Financial institutions can also rely on tools like Amazon Textract to remove any human-based errors from manual data entry and ensure everyone gets a fair loan assessment.
How can AWS support your OCR needs?
Businesses that make the most of OCR can expedite document processing, rapidly collect data from forms, and improve any business processes that rely on written, handwritten, or scanned documents. Amazon Textract can detect printed text and handwriting in English, German, French, Spanish, Italian, and Portuguese. It can extract explicitly implied data, labeled data, and line items from an itemized list of goods or services from almost any invoice or receipt without any templates or configuration. You can also access several advanced features for use case-specific customization and more..
Get started with OCR software with AWS by creating a free account today.