address dybe 2210 1776 prs

Author: laujan

articles/ai-services/content-understanding/image/overview.md

@@ -1,13 +1,13 @@
 ---
 title: Azure AI Content Understanding image overview
 titleSuffix: Azure AI services
-description: Learn about Azure AI Content Understanding image solutions
+description: Learn how to use Azure AI Content Understanding image solutions
 author: laujan
 ms.author: lajanuar
 manager: nitinme
 ms.service: azure-ai-content-understanding
-ms.topic: overview
-ms.date: 01/14/2025
+ms.topic: how-to
+ms.date: 11/19/2024
 ms.custom: ignite-2024-understanding-release
 ---
 
@@ -16,10 +16,10 @@ ms.custom: ignite-2024-understanding-release
 > [!IMPORTANT]
 >
 > * Azure AI Content Understanding is available in preview. Public preview releases provide early access to features that are in active development.
-> * Features, approaches, and processes can change or present constrained capabilities, before General Availability (GA).
+> * Features, approaches, and processes may change or have constrained capabilities, prior to General Availability (GA).
 > * For more information, *see* [**Supplemental Terms of Use for Microsoft Azure Previews**](https://azure.microsoft.com/support/legal/preview-supplemental-terms).
 
-Azure AI Content Understanding standardizes the extraction of data from images, making it easier to analyze large volumes of unstructured data. Standardized extraction speeds up time-to-value and simplifies integration into downstream analytical workflows. With the Content Understanding APIs, you can define a schema to specify the fields, descriptions, and output types for extraction. The service then analyses the images and provides structured data, which can be applied in various use cases, such as:
+Azure AI Content Understanding standardizes the extraction of data from images, making it easier to analyze large volumes of unstructured data. Standardized extraction speeds up time-to-value and simplifies integration into downstream analytical workflows. With the Content Understanding APIs, you can define schema to specify the fields, descriptions, and output types for extraction. The service then analyses the images and provides structured data, which can be applied in various use cases, such as:
 
 * **Retrieval-augmented generation (RAG) applications:** Extract key details from your images to build a robust index that powers user-facing chat experiences. This index enables users to ask questions and receive accurate answers based on the content of your images.
 
@@ -45,8 +45,8 @@ For detailed information on supported input file formats, refer to our [Service
 
 > [!NOTE]
 > For best results, image schema should only be used to process non-document-based images.
-> Text-heavy images of documents should be processed using a document schema.
-> Use cases that require extraction of text from document images or scanned documents should be processed with a document field extraction schema.
+> Text heavy images of documents should be processed using a document schema.
+> Use cases that require extraction of text from document images or scanned documents in image formats should be processed using a document field extraction schema.
 
 ## Supported languages and regions
 For a detailed list of supported languages and regions, visit our [Language and region support](../language-region-support.md) page.
@@ -59,7 +59,7 @@ For detailed information on supported field types, refer to our [Service quotas
 As with all the Azure AI services, developers using the Content Understanding service should be aware of Microsoft's policies on customer data. See our [**Data, protection and privacy**](https://www.microsoft.com/trust-center/privacy) page to learn more.
 
 > [!IMPORTANT]
-> If you're using Microsoft products or services to process Biometric Data, you're responsible for: (i) providing notice to data subjects, including with respect to retention periods and destruction; (ii) obtaining consent from data subjects; and (iii) deleting the Biometric Data, all as appropriate, and required under applicable Data Protection Requirements. "Biometric Data" have the meaning articulated in Article 4 of the GDPR and, if applicable, equivalent terms in other data protection requirements. For related information, see [Data and Privacy for Face](/legal/cognitive-services/face/data-privacy-security).
+> If you are using Microsoft products or services to process Biometric Data, you are responsible for: (i) providing notice to data subjects, including with respect to retention periods and destruction; (ii) obtaining consent from data subjects; and (iii) deleting the Biometric Data, all as appropriate and required under applicable Data Protection Requirements. "Biometric Data" will have the meaning set forth in Article 4 of the GDPR and, if applicable, equivalent terms in other data protection requirements. For related information, see [Data and Privacy for Face](/legal/cognitive-services/face/data-privacy-security).
 
 ## Next steps