OCR Engine Evolution – ACMO – Invoice Automation Australia
In today's blog post, I wanted to deep dive into the cognitive machine reading software available today, its history and traditional use, and who is leading the future of cloud capture technology.
What is OCR cognitive machine reading?
Essentially, Intelligent document processing.
OCR is used across industries and departments for various business processes due to its flexibility and efficiency as a scanning tool for eliminating data entry and capturing information. Intelligent document processing OCR is part of the technology involved in AP automation, digital mailroom automation, customer onboarding, records digitisation for forms & claims processing, and more.
The Key Players
The key players in today's Optical character recognition (OCR) industry include Kofax, ABBYY, and Ephesoft, with close market contenders including IBM Datacap, Rossum, AWS Textract, Nanonets, Google Document AI and Azure Form Recognizer.
Maybe you want to know: Kofax Agility vs Kofax AP Essentials
ABBYY FineReader PDF
Convert, edit, share, and collaborate on PDFs and scans in the digital workplace. FineReader PDF empowers professionals to maximise efficiency in the digital workplace. Featuring ABBYY's latest AI-based OCR technology, FineReader PDF makes it easier to digitise, retrieve, edit, protect, share, and collaborate on documents in the same workflow.
Kofax OmniPage OCR software converts any document into the word processor format of your choice. Save, edit and search documents as you would a Word document. OmniPage solutions are perfect for a single user, small business or enterprise and include superior conversion accuracy, intelligent character recognition & zonal recognition, and fast document conversion times.
Intelligent Document Processing (IDP)- Ephesoft's software service extracts important data from digital and physical documents through data capture technology. IDP is the best way to streamline your document management. Competitive advantages include simplified data privacy and compliance, highly-scalable document processing, improved time and money savings, increased efficiency and satisfied employees and a better foundation for digital transformation.
History and traditional use of OCR
What is OCR and how did it come about?
The earliest use of optical character recognition can be traced back to telegraphy technology and reading devices for the blind. Emanuel Goldberg invented the OCR-like machine. It read characters and converted them into standard telegraphic code.
Around the same time, Edmund Fournier d'Albe invented the Optophone. Like Goldberg's invention, this was a handheld scanner that produced tones corresponding to specific letters or characters as it moved across a page.
Throughout the late 1920s into the early 1930s, Goldberg developed a machine for searching microfilm archives using optical code recognition. He called it his "Statistical Machine." In 1931, he patented this invention which IBM later acquired.
OMR stands for "Optical Mark Recognition"
OMR allows you to read any "fill-in-the-bubble" type forms. It was invented for use on tests, surveys, elections, questionnaires, and course evaluations. Traditionally, OMR forms were read using specialised scanners and forms and often required respondents to use special pencils to fill in those forms. You likely had this experience in school on tests where you had to fill in the ovals with a no.2 pencil. OMR successfully processed large volumes of documents with accuracy and saved them safely. Big industry also used OMR to keep inventory count; with an OMR reader, it became easy and systematic.
OCR stands for "Optical Character Recognition"
OCR allows you to read machine-printed characters and is a technology that enables you to convert different types of documents, such as scanned paper documents, PDF files or images captured by a digital camera, into editable and searchable data. OCR is an essential tool for businesses working on digitising information gathered from documents or photographs into an electronic system, and it's especially useful for processing data in large quantities of documents.
ICR stands for "Intelligent Character Recognition"
ICR allows you to read handwritten text. ICR is quite powerful but is the least accurate of the three technologies as there are so many variables when reading handwriting. Sometimes even humans have difficulty reading another person's handwriting. In forms processing, ICR is great for reading comments from their respondents or for reading names, addresses, or other similar demographic data handwritten on forms.
The future of new cloud capture technology
How is OCR powering the future of work? In addition to improving file searchability and data entry speed, OCR also enables developing technologies like AI and machine learning to improve the jobs of employees dealing with information-heavy business processes by eliminating redundant and time-consuming manual tasks. It's a critical factor in an organisation's digital transformation.
The next-generation leaders
Amazon Textract makes adding document text detection and analysis to your applications easy. Using Amazon Textract, customers can:
- Detect typed and handwritten text in various documents, including financial reports, medical records, and tax forms.
- Extract text, forms, and tables from documents with structured data, using the Amazon Textract Document Analysis API.
- Specify and extract information from documents using the Queries feature within the Amazon Textract Analyze Document API.
- Process invoices and receipts with the AnalyzeExpense API.
- Process ID documents such as drivers' licenses and passports issued by the U.S. government using the AnalyzeID API.
Amazon Textract is based on the same proven, highly scalable, deep-learning technology developed by Amazon's computer vision scientists to analyse billions of images and videos daily. You don't need any machine learning expertise to use it. Amazon Textract includes simple, easy-to-use APIs that can analyse image files and PDF files. Amazon Textract is constantly learning from new data, and Amazon is continually adding new features to the service.
Microsoft Azure Form Recognizer
Azure Form Recognizer is a cloud-based Azure Applied AI Service that uses machine-learning models to extract key-value pairs, text, and tables from your documents. Form Recogniser analyses your forms and documents extracts text and data, maps field relationships as key-value pairs, and returns a structured JSON output. You quickly get accurate results tailored to your specific content without excessive manual intervention or extensive data science expertise. Use Form Recogniser to automate your data processing in applications and workflows, enhance data-driven strategies, and enrich document search capabilities.
Google Document AI
Document AI is built on decades of AI innovation at Google, bringing powerful and useful solutions to these challenges. Under the hood are Google's industry-leading technologies: computer vision (including OCR) and natural language processing (NLP) that create pre-trained models for high-value, high-volume documents. DocAI has already processed tens of billions of documents across lending, insurance, government and other industries.
The DocAI platform is a unified console for document processing that lets you quickly access all parsers and tools. You can automate and validate documents from the platform to streamline workflows, reduce guesswork, and keep data accurate and compliant.
Validate and enrich parsed information with Google Knowledge Graph to make the data even more useful, checking company names, addresses, phone numbers, and other details against entities on the internet.
Human-in-the-Loop AI is a new DocAI feature that will help companies achieve higher document processing accuracy with the assurance of human review. Adding human review can increase accuracy and help businesses interpret predictions using purpose-built tools to enable those reviews.
Want to get cognitive machine reading software to help your business with document processing?
Take the next step in starting your digital transformation using intelligent automation today.