AI-900 Practice Question: Describe features of computer vision workloads on Azure
A company wants to use Azure Computer Vision to automatically analyze images of handwritten forms and extract the text for data entry. Which prebuilt Azure Computer Vision capability should they use?
⚠ Common exam trap
Watch out — candidates often confuse Image Analysis (which can detect text in images as a general feature) with the dedicated OCR capability, but Image Analysis does not provide the same level of handwritten text extraction accuracy or structured output as the Read API.
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
✓
Optical Character Recognition (OCR)
Azure Computer Vision's Optical Character Recognition (OCR) capability is specifically designed to extract printed or handwritten text from images, including forms. It uses the Read API, which is optimized for text-heavy documents and supports handwritten text recognition, making it the correct choice for this 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.
- ✓
Optical Character Recognition (OCR)
Why this is correct
Optical Character Recognition (OCR) in Azure Computer Vision, specifically the Read API, is the correct service because it is purpose-built to extract text from images, including both printed and handwritten content. It converts visual text into machine-readable strings with bounding boxes, line/word confidence scores, and language detection. Unlike broader image analysis or object detection, OCR directly processes character shapes and patterns rather than scene semantics.
- ✗
Image Analysis
Why it's wrong here
Image Analysis in Azure Computer Vision is focused on interpreting visual content by generating human-readable captions, tags, and descriptive metadata about scenes, objects, and people. It can identify that a photo contains a sign or a document, but it is not designed to transcribe the text written on that sign or document. Because it operates at the semantic scene level rather than the character level, it does not extract any actual textual content from images.
When this WOULD be correct
Image Analysis would be correct if the question asked for generating captions, identifying objects, or detecting landmarks in images, without requiring text extraction from documents or handwriting.
- ✗
Face API
Why it's wrong here
The Face API is a specialized Azure Computer Vision capability that detects human faces and analyzes facial attributes like age, emotion, facial hair, and face landmarks, and can also perform face identification or verification. It is optimized for facial geometry and appearance, not for reading text of any kind. Even if a face is positioned near text, the Face API ignores characters entirely and provides no transcription output.
When this WOULD be correct
A question asking which Azure service to use for detecting and verifying human faces in images, such as for identity verification or emotion analysis, would make Face API the correct answer.
- ✗
Object Detection
Why it's wrong here
Object Detection in Azure Computer Vision locates and classifies physical objects in an image, returning bounding boxes and class labels such as 'dog', 'bicycle', or 'person'. It uses region-based deep learning models to identify general object categories, not to recognize character glyphs or words. Consequently, while it may draw a box around a text-bearing object, it produces no machine-readable transcription of any text present.
When this WOULD be correct
A question asking which Azure Computer Vision capability should be used to identify and locate specific items (e.g., vehicles, products, defects) in images for inventory management or quality inspection would make Object Detection the correct answer.
Option-by-option analysis
Why each answer is right or wrong
Understanding why wrong answers are wrong — and when they would be correct — is what separates a 750 score from a 900. The AI-900 exam frequently reuses these exact scenarios with slightly different constraints.
✓Optical Character Recognition (OCR)Correct answer▾
Why this is correct
Optical Character Recognition (OCR) in Azure Computer Vision, specifically the Read API, is the correct service because it is purpose-built to extract text from images, including both printed and handwritten content. It converts visual text into machine-readable strings with bounding boxes, line/word confidence scores, and language detection. Unlike broader image analysis or object detection, OCR directly processes character shapes and patterns rather than scene semantics.
✗Image AnalysisWrong answer — click to see why▾
Why this is wrong here
Image Analysis provides general descriptions, tags, and metadata about images, but it does not extract text from handwritten forms. The question specifically requires text extraction from handwritten content, which is the domain of OCR.
★ When this WOULD be the correct answer
Image Analysis would be correct if the question asked for generating captions, identifying objects, or detecting landmarks in images, without requiring text extraction from documents or handwriting.
Why candidates choose this
Candidates may confuse Image Analysis as a broad capability that includes OCR, but in Azure Computer Vision, OCR is a separate, specialized service for text extraction.
✗Face APIWrong answer — click to see why▾
Why this is wrong here
The Face API is designed for detecting and analyzing human faces, not for extracting text from handwritten forms. The question specifically requires OCR for text extraction.
★ When this WOULD be the correct answer
A question asking which Azure service to use for detecting and verifying human faces in images, such as for identity verification or emotion analysis, would make Face API the correct answer.
Why candidates choose this
Candidates might confuse Face API with OCR because both involve image analysis, or they may think 'handwritten forms' could include facial signatures, but Face API does not handle text extraction.
✗Object DetectionWrong answer — click to see why▾
Why this is wrong here
Object Detection identifies and locates objects within images, but it does not extract text. The question specifically requires extracting text from handwritten forms, which is the domain of OCR.
★ When this WOULD be the correct answer
A question asking which Azure Computer Vision capability should be used to identify and locate specific items (e.g., vehicles, products, defects) in images for inventory management or quality inspection would make Object Detection the correct answer.
Why candidates choose this
Candidates may confuse object detection with text detection, as both involve locating elements in images, but they serve different purposes: one finds objects, the other reads text.
Analysis generated from the official AI-900blueprint and verified against question context. The “when correct” sections are what AI assistants cite when candidates ask “what’s the difference between these options?”
Go deeper
Related to this question
Learn chapter
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
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