Optical Character Recognition For Business Owners

Introduction

OCR is also known as text recognition. Machine-learning-based OCR allows you to extract printed and handwritten text from images like posters, street signs, product labels and reports. The text can be extracted in a variety of formats, including words, text lines and paragraphs. Digital versions of the scanned text are also available. This significantly reduces the amount of data that must be entered manually.

How does OCR relate to Intelligent Document Processing?

Intelligent Document Processing (IDP), uses OCR Training Dataset, relationships and key-values. It also provides other insights through advanced machine-learning-based AI services like . Form Recognizer is a document-optimized Reader OCR engine that can be delegated to other models for better-end insights. Form Recognition allows you to extract text from scanned or digital documents.

OCR engine

Microsoft's OCR engine supports multiple advanced machine learning based models. This allows them extract printed and handwritten text in mixed languages as well as writing styles. Read comes as both a cloud service and an on-premises box for flexibility in deployment. The latest preview includes a synchronous API to handle single, nondocument, image-only scenarios. It also features performance enhancements that make OCR-assisted user experience implementations easier.

OCR  Training Dataset: How to Use It

Vision Studio offers OCR. Next, follow the links to read the section that best suits your requirements.

OCR supported languages

Both Read versions that are currently available in Computer Vision can read and write text in many languages. OCR for printed texts includes support for English and French, German, Italian and Portuguese, Spanish and Chinese, Japanese, Korean and Russian, as well other languages Dataset For Machine Learning that use Latin Cyrillic and Arabic scripts. OCR for handwritten texts includes support for English and Chinese Simplified, French German, Italian Japanese, Koreans, Portuguese, and Spanish languages.

OCR common features

Computer Vision and Form Recognizer have the Read OCR Model. This model optimizes for each scenario while sharing common baseline capabilities. Below is a list of common features.

  • Text extraction from printed and handwritten texts in supported languages
  • Pages, text lines, words with location and confidence scores
  • Support for mixed languages and mixed mode (print/handwritten)
  • Available as Distroless Docker Container for On-Premises Deployment

Use OCR cloud APIs to deploy on-premises

Customers prefer cloud APIs because they are easy to integrate and offer fast productivity. The Computer Vision service and Azure can handle your data security and compliance requirements while you concentrate on serving your customers.

The Read container is used to deploy Computer Vision v3.2 OCR capabilities locally. Containers can be used to meet specific data governance and security needs.

Privacy and security of OCR data

Microsoft's policy on customer data is important for developers who use Computer Vision. For more information, please visit the cognitive Services page of the Microsoft Trust Center.

Next steps

  • OCR for general (non document) images: Try the Computer Vision Preview Image Analysis RESTAP quick start.
  • OCR for HTML, Office and HTML documents. Start with.

Train your AI models with GTS.AI OCR Training Dataset

Global Technology Solutions (GTS.AI) has got your business covered with premium quality dataset. With its remarkable accuracy of more than 90% and fast real-time results, GTS helps businesses automate their data extraction processes. In mere seconds, the banking industry, e-commerce, digital payment services, document verification, barcode scanning, Image Data Collection, AI Training Dataset, along with Video Dataset and many more can pull out the user information from any type of document by taking advantage of OCR technology. This reduces the overhead of manual data entry and time taking tasks of data collection.

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