Practice Questions

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Question 1

A company wants to convert scanned paper documents into searchable digital text. Which computer vision solution should be used?

A. Image classification
B. Object detection
C. Optical character recognition (OCR)
D. Image segmentation

Correct Answer: C

Explanation:
OCR extracts text from images and scanned documents, converting it into machine-readable text.

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Question 2

Which output is typically produced by an OCR solution?

A. Image labels with confidence scores
B. Bounding boxes around detected objects
C. Extracted text and its location in the image
D. Pixel-level image masks

Correct Answer: C

Explanation:
OCR outputs recognized text along with positional information, often as bounding boxes.

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Question 3

Which scenario is the best fit for OCR?

A. Counting vehicles in traffic images
B. Categorizing images as indoor or outdoor
C. Extracting invoice numbers from scanned receipts
D. Detecting faces in photos

Correct Answer: C

Explanation:
OCR is designed to extract text, such as invoice numbers, from images or documents.

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Question 4

Which Azure service provides prebuilt OCR capabilities without requiring model training?

A. Azure AI Vision
B. Azure Machine Learning
C. Azure AI Custom Vision
D. Azure OpenAI

Correct Answer: A

Explanation:
Azure AI Vision includes prebuilt OCR features that can recognize text in images and documents.

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Question 5

What is a key difference between OCR and object detection?

A. OCR identifies object locations
B. Object detection extracts text
C. OCR converts visual text into machine-readable text
D. Object detection does not use machine learning

Correct Answer: C

Explanation:
OCR focuses on extracting and converting text, while object detection identifies and locates objects.

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Question 6

Which type of text can OCR solutions typically recognize?

A. Printed text only
B. Handwritten text only
C. Printed and handwritten text
D. Spoken language

Correct Answer: C

Explanation:
Modern OCR solutions can recognize both printed and handwritten text, though accuracy may vary.

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Question 7

Which Azure service builds on OCR to extract structured information from forms and documents?

A. Azure AI Vision
B. Azure AI Document Intelligence
C. Azure Cognitive Search
D. Azure Machine Learning

Correct Answer: B

Explanation:
Azure AI Document Intelligence extends OCR capabilities to analyze forms, invoices, and receipts.

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Question 8

Which phrase in an exam question most strongly indicates an OCR solution?

A. “Classify images by category”
B. “Detect and locate objects”
C. “Extract text from scanned documents”
D. “Analyze facial expressions”

Correct Answer: C

Explanation:
Keywords such as extract text, recognize text, or scan documents point directly to OCR.

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Question 9

What responsible AI consideration is most relevant when using OCR on documents?

A. Object bias
B. Data privacy and security
C. Bounding box accuracy
D. Image resolution

Correct Answer: B

Explanation:
OCR often processes documents containing sensitive personal or business information, making privacy and security critical.

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Question 10

Which statement correctly describes OCR solutions on Azure?

A. They only work with handwritten documents
B. They require custom training for every use case
C. They convert images of text into digital text
D. They are used to detect objects in images

Correct Answer: C

Explanation:
OCR solutions convert visual representations of text into machine-readable digital text.

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Final AI-900 Exam Pointers

• OCR = read text from images
• Look for keywords: scan, read, extract text, digitize
• Azure AI Vision = prebuilt OCR
• Azure AI Document Intelligence = structured document extraction

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Go to the AI-900 Exam Prep Hub main page.

Overview

Optical Character Recognition (OCR) is a core computer vision workload tested on the AI-900 exam. OCR solutions are designed to extract printed or handwritten text from images and documents and convert it into machine-readable text.

On the AI-900 exam, you are expected to:

• Recognize OCR use cases
• Understand what OCR does and does not do
• Identify Azure services that provide OCR capabilities

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What Is Optical Character Recognition (OCR)?

OCR is a computer vision technique that:

• Detects text within images
• Extracts characters, words, and lines
• Converts visual text into digital text

It answers the question:

“What text appears in this image or document?”

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Key Characteristics of OCR Solutions

1. Text Extraction

OCR solutions can extract:

• Printed text
• Handwritten text (depending on the service)
• Numbers, symbols, and punctuation

The output is searchable and editable text.

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2. Language Support

OCR solutions typically:

• Support multiple languages
• Automatically detect language in many cases

This is important for global document processing scenarios.

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3. Layout and Structure Awareness

Advanced OCR solutions can identify:

• Lines and paragraphs
• Tables
• Forms
• Key-value pairs

This enables downstream document processing and automation.

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4. Bounding Boxes for Text

OCR can return:

• Extracted text
• Bounding boxes showing where text appears

This allows applications to highlight or validate text locations.

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5. Image and Document Input

OCR works with:

• Images (JPG, PNG)
• Scanned documents
• PDFs
• Photos taken by mobile devices

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Common OCR Scenarios

OCR is the correct solution when text extraction is the primary goal.

Typical Use Cases

• Invoice and receipt processing
• Digitizing scanned documents
• License plate recognition
• Form processing
• Reading text from signs or labels

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OCR vs Other Computer Vision Workloads

Understanding this distinction is critical for AI-900.

Task	Primary Purpose
Image classification	Categorize entire images
Object detection	Locate and identify objects
OCR	Extract text from images
Image segmentation	Classify pixels

Exam Tip:
If the question mentions read, extract, recognize text, or digitize documents, OCR is the correct answer.

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Azure Services for OCR

Azure AI Vision (OCR Capabilities)

• Provides prebuilt OCR models
• Extracts printed and handwritten text
• Supports multiple languages
• No training required
• Accessible via REST APIs

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Azure AI Document Intelligence (formerly Form Recognizer)

• Builds on OCR to:
  • Extract structured data
  • Analyze forms and documents
• Commonly used for:
  • Invoices
  • Receipts
  • Business documents

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Features of OCR Solutions on Azure

Prebuilt Models

• Ready to use
• No custom training needed
• Ideal for common document scenarios

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Scalable Cloud Processing

• Runs in Azure
• Handles large document volumes
• Integrates with automation workflows

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Integration with Other Services

OCR outputs are often used with:

• Search services
• Databases
• Business process automation
• AI-powered document workflows

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When to Use OCR

Use OCR when:

• Text needs to be extracted from images or documents
• Manual data entry must be reduced
• Documents need to be searchable

When Not to Use OCR

• When identifying objects rather than text
• When categorizing images without text extraction
• When pixel-level image analysis is required

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Responsible AI Considerations

At a fundamentals level, AI-900 expects awareness of:

• Privacy when processing documents with personal data
• Security of stored text and documents
• Accuracy limitations, especially with handwritten or low-quality images

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Key Exam Takeaways

• OCR extracts text from images
• Converts visual content into machine-readable text
• Supports multiple languages
• Azure AI Vision provides OCR capabilities
• Azure AI Document Intelligence extends OCR for forms
• Watch for keywords: read, extract, recognize text, scan

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