- A
Object detection
Why wrong: Object detection identifies and locates objects within an image, not text.
- B
OCR (Read API)
Correct. The Read API extracts printed text from images and documents.
- C
Semantic segmentation
Why wrong: Semantic segmentation classifies every pixel in an image into a category, not text extraction.
- D
Image Analysis (description generation)
Why wrong: Image Analysis can describe the content of an image but does not extract specific text.
Quick Answer
The answer is the OCR (Read API) within Azure Computer Vision. This capability is correct because it is specifically designed to extract printed and handwritten text from images and documents, using deep-learning-based algorithms to read text in various formats and orientations, which is exactly what is needed for processing receipt images in expense reports. On the Microsoft Azure AI Fundamentals AI-900 exam, this question tests your understanding of the distinct Computer Vision pre-built capabilities, often contrasting the OCR Read API with features like Optical Character Recognition (the older OCR service) or image analysis APIs that describe scenes but do not extract text. A common trap is confusing the general “OCR” label with the newer, more powerful “Read API,” so remember that for receipt processing you need the Read API, which is the modern, scalable solution for text extraction. A helpful memory tip: think “Read the Receipt” to link the Read API directly to extracting printed text from receipts.
AI-900 Practice Question: Describe features of computer vision workloads on Azure
This AI-900 practice question tests your understanding of describe features of computer vision workloads on azure. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company wants to automate the processing of expense reports by extracting printed text from images of receipts. Which Azure Computer Vision capability should they use?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
OCR (Read API)
The OCR (Read API) is the correct Azure Computer Vision capability for extracting printed text from images of receipts. It is specifically designed to detect and extract text from images and documents, supporting both printed and handwritten text, making it ideal for automating expense report processing.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Object detection
Why it's wrong here
Object detection identifies and locates objects within an image, not text.
- ✓
OCR (Read API)
Why this is correct
Correct. The Read API extracts printed text from images and documents.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Semantic segmentation
Why it's wrong here
Semantic segmentation classifies every pixel in an image into a category, not text extraction.
- ✗
Image Analysis (description generation)
Why it's wrong here
Image Analysis can describe the content of an image but does not extract specific text.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse object detection (which finds objects like a receipt) with OCR (which reads the text on the receipt), leading them to select object detection for a text extraction task.
Detailed technical explanation
How to think about this question
The OCR Read API uses deep learning models trained on millions of images to recognize text in various fonts, layouts, and lighting conditions. It returns results with bounding boxes, confidence scores, and structured text output, enabling downstream processing like automated data entry into expense systems. In real-world scenarios, the API can handle skewed or partially occluded text on crumpled receipts, which is critical for reliable automation.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
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FAQ
Questions learners often ask
What does this AI-900 question test?
Describe features of computer vision workloads on Azure — This question tests Describe features of computer vision workloads on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: OCR (Read API) — The OCR (Read API) is the correct Azure Computer Vision capability for extracting printed text from images of receipts. It is specifically designed to detect and extract text from images and documents, supporting both printed and handwritten text, making it ideal for automating expense report processing.
What should I do if I get this AI-900 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 11, 2026
This AI-900 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-900 exam.
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