Merge pull request #216167 from sanjeev3/main

SEO refresh to FR Identity and CV OCR concept pages

Author: prmerger-automator[bot]

articles/applied-ai-services/form-recognizer/concept-id-document.md

@@ -1,7 +1,7 @@
 ---
-title: Form Recognizer Identity Document (ID) model
+title: Identity document (ID) processing – Form Recognizer
 titleSuffix: Azure Applied AI Services
-description: Concepts related to data extraction and analysis using the prebuilt ID document model and extracting information from identity documents with OCR and AI.
+description: Automate identity document (ID) processing of driver licenses, passports, and more with Form Recognizer.
 author: laujan
 manager: nitinme
 ms.service: applied-ai-services
@@ -24,7 +24,13 @@ ms.custom: references.regions
 [!INCLUDE [applies to v2.1](includes/applies-to-v2-1.md)]
 ::: moniker-end
 
-The ID document model combines Optical Character Recognition (OCR) with deep learning models to analyze and extract key information from identity documents: US Drivers Licenses (all 50 states and District of Columbia), international passport biographical pages, US state IDs, social security cards, and permanent resident cards and more. The API analyzes identity documents, extracts key information, and returns a structured JSON data representation.
+## What is identity document (ID) processing
+
+Identity document (ID) processing involves extraction of data from identity documents whether manually or using OCR based techniques. Examples of identity documents include passports, driver licenses, resident cards, and national identity cards like the social security card in the US. It is an important step in any business process that requires some proof of identity. Examples include customer verification in banks and other financial institutions, mortgage applications, medical visits, claim processing, hospitality industry, and more. Individuals provide some proof of their identity via driver licenses, passports, and other similar documents so that the business can efficiently verify them before providing services and benefits.
+
+## Form Recognizer Identity document (ID) model
+
+The Form Recognizer Identity document (ID) model combines Optical Character Recognition (OCR) with deep learning models to analyze and extract key information from identity documents: US Drivers Licenses (all 50 states and District of Columbia), international passport biographical pages, US state IDs, social security cards, and permanent resident cards and more. The API analyzes identity documents, extracts key information, and returns a structured JSON data representation.
 
 ***Sample U.S. Driver's License processed with [Form Recognizer Studio](https://formrecognizer.appliedai.azure.com/studio/prebuilt?formType=idDocument)***
 

articles/cognitive-services/Computer-vision/overview-ocr.md

@@ -1,5 +1,5 @@
 ---
-title: What is Optical character recognition?
+title: What is Optical Character Recognition (OCR)?
 titleSuffix: Azure Cognitive Services
 description: The optical character recognition (OCR) service extracts print and handwritten text from images.
 services: cognitive-services
@@ -14,13 +14,13 @@ ms.author: pafarley
 ms.custom: seodec18, devx-track-csharp, ignite-2022
 ---
 
-# What is Optical character recognition?
+# What is Optical Character Recognition (OCR)
 
-Optical character recognition (OCR) allows you to extract printed or handwritten text from images, such as posters, street signs and product labels, as well as from documents like articles, reports, forms, and invoices. 
+OCR or Optical Character Recognition is also referred to as text recognition or text extraction. Machine-learning based OCR techniques allow you to extract printed or handwritten text from images, such as posters, street signs and product labels, as well as from documents like articles, reports, forms, and invoices. The text is typically extracted as words, text lines, and paragraphs or text blocks, enabling access to digital version of the scanned text. This eliminates or significantly reduces the need for manual data entry.
 
-## How is OCR related to intelligent document processing (IDP)?
+## How is OCR related to Intelligent Document Processing (IDP)?
 
-OCR typically refers to the foundational technology focusing on extracting text while delegating the extraction of structure, relationships, key-values, entities, and other document-centric insights to intelligent document processing service like [Form Recognizer](../../applied-ai-services/form-recognizer/overview.md). Form Recognizer includes a document-optimized version of **Read** as its OCR engine while delegating to other models for higher-end insights. If you are extracting text from scanned and digital documents, use [Form Recognizer Read OCR](../../applied-ai-services/form-recognizer/concept-read.md).
+Intelligent Document Processing (IDP) uses OCR as its foundational technology to additionally extract structure, relationships, key-values, entities, and other document-centric insights with an advanced machine-learning based AI service like [Form Recognizer](../../applied-ai-services/form-recognizer/overview.md). Form Recognizer includes a document-optimized version of **Read** as its OCR engine while delegating to other models for higher-end insights. If you are extracting text from scanned and digital documents, use [Form Recognizer Read OCR](../../applied-ai-services/form-recognizer/concept-read.md).
 
 ## Read OCR engine
 Microsoft's **Read** OCR engine is composed of multiple advanced machine-learning based models supporting [global languages](./language-support.md). This allows them to extract printed and handwritten text including mixed languages and writing styles. **Read** is available as cloud service and on-premises container for deployment flexibility. With the latest preview, it's also available as a synchronous API for single, non-document, image-only scenarios with performance enhancements that make it easier to implement OCR-assisted user experiences.