AI-900 Practice Question: Describe features of computer vision workloads on Azure
A logistics company needs to automatically extract printed and handwritten text from scanned shipping labels. Which Azure Computer Vision capability should they use?
⚠ Common exam trap
Watch out — candidates often confuse Azure Custom Vision with OCR capabilities, assuming it can be trained for text extraction, but Custom Vision is limited to object detection and classification, not text recognition.
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
✓
Azure Computer Vision Read API
The Azure Computer Vision Read API is specifically designed to extract printed and handwritten text from images and documents, such as scanned shipping labels. It uses optical character recognition (OCR) to process text in various languages and formats, making it the correct choice for this logistics scenario.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Azure Face API
Why it's wrong here
Azure Face API is a specialized service for detecting, analyzing, and recognizing human faces in images. It returns attributes like age, emotion, and a unique face identifier, but it performs no optical character recognition (OCR) whatsoever, so it cannot extract printed text from a shipping label.
- ✓
Azure Computer Vision Read API
Why this is correct
Azure Computer Vision Read API is the correct service because it performs OCR (optical character recognition) optimized for extracting both printed and handwritten text from images and documents. It can handle shipping labels, reading text in various orientations, and returns structured output with bounding boxes and confidence scores, making it suitable for automated logistics workflows.
- ✗
Azure Custom Vision
Why it's wrong here
Azure Custom Vision is a tool for training custom image classification and object detection models using labeled images. It does not have built-in OCR capabilities; it only identifies what objects or scenes are present (e.g., 'label' vs. 'package'), not the textual content on the label. To extract text, you would need to pair Custom Vision with a separate OCR service.
- ✗
Azure Video Indexer
Why it's wrong here
Azure Video Indexer is designed to analyze video and audio content, extracting insights such as spoken transcripts, faces, and on-screen text appearing in video frames. It is not intended for static images like shipping labels, and using it for single-image OCR would be inefficient and out of scope, whereas Computer Vision Read API is the direct, purpose-built solution.
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Related to this question
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Azure Machine Learning Studio
Key term
OCR
Optical Character Recognition is technology that converts images of text, like scanned documents or photos, into machine-readable text data.
Key term
Computer vision
Computer vision is a field of artificial intelligence that enables computers to interpret and make decisions based on visual data from the world, such as images and videos.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.