AI-900 Practice Question: Describe features of computer vision workloads on Azure
A logistics company wants to automatically extract the tracking numbers, delivery addresses, and sender names from scanned shipping labels. Which prebuilt Azure Computer Vision capability should they use?
⚠ Common exam trap
Many candidates confuse Object Detection (which finds objects) with OCR (which finds text), or assume Image Classification can read text, when in fact only OCR is designed for text extraction from images.
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)
(Optical Character Recognition, or OCR) is correct because the task requires extracting text (tracking numbers, addresses, sender names) from scanned images. Azure Computer Vision's OCR API is specifically designed to detect and read printed or handwritten text from images, returning the text content along with bounding boxes. Object Detection, Image Classification, and Face Detection do not extract text, making OCR the appropriate prebuilt capability.
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 localizes instances of predefined object classes by drawing bounding boxes around them, such as 'package' or 'box', using models like a region-based CNN. Its output is spatial coordinates and class labels, not the alphanumeric content inside the detected area, so it cannot extract the tracking number from the label text. Consequently, it is not suited to character-level information retrieval.
When this WOULD be correct
If the question asked for identifying the presence and location of shipping label elements (e.g., barcode, logo) without reading text, Object Detection would be correct.
- ✓
Optical Character Recognition (OCR)
Why this is correct
Optical Character Recognition (OCR) is the correct choice because it is specifically designed to digitize printed or handwritten text from images. Azure's Computer Vision OCR/Read API detects text regions, recognizes characters, and returns a machine-readable string, enabling automatic extraction of tracking numbers from shipping labels without manual data entry. This makes it the only option that directly addresses the requirement of reading text from an image.
- ✗
Image Classification
Why it's wrong here
Image Classification assigns a single categorical label to an entire image, such as 'shipping-label' or 'parcel-photo', by analyzing dominant visual patterns. It does not produce any text output or locate specific regions, so while it could classify the type of document, it cannot read the actual tracking number printed on it. Therefore it is incorrect for extracting the tracking identifier.
When this WOULD be correct
A question asking which Azure Computer Vision capability can determine whether an image contains a shipping label, a receipt, or a document — without needing to read the text — would make Image Classification the correct answer.
- ✗
Face Detection
Why it's wrong here
Face Detection is a specialized computer vision task that locates human faces in images and returns bounding box coordinates, often used for identity verification or emotion recognition. It has no capability to interpret text characters, and tracking labels typically contain no faces. Thus, it is wholly irrelevant to extracting a tracking number, and therefore incorrect for this use case.
When this WOULD be correct
A question asking: 'Which Computer Vision service can be used to detect and locate human faces in an image for security surveillance?' would make Face Detection correct.
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) is the correct choice because it is specifically designed to digitize printed or handwritten text from images. Azure's Computer Vision OCR/Read API detects text regions, recognizes characters, and returns a machine-readable string, enabling automatic extraction of tracking numbers from shipping labels without manual data entry. This makes it the only option that directly addresses the requirement of reading text from an image.
✗Object DetectionWrong answer — click to see why▾
Why this is wrong here
Object Detection identifies and locates objects within an image (e.g., boxes, vehicles), but it cannot read or extract text like tracking numbers or addresses from labels.
★ When this WOULD be the correct answer
If the question asked for identifying the presence and location of shipping label elements (e.g., barcode, logo) without reading text, Object Detection would be correct.
Why candidates choose this
Candidates may confuse Object Detection with OCR because both involve locating items in images, but Object Detection does not perform text extraction.
✗Image ClassificationWrong answer — click to see why▾
Why this is wrong here
Image Classification assigns a single label to an entire image (e.g., 'shipping label'), but it cannot extract specific text fields like tracking numbers or addresses.
★ When this WOULD be the correct answer
A question asking which Azure Computer Vision capability can determine whether an image contains a shipping label, a receipt, or a document — without needing to read the text — would make Image Classification the correct answer.
Why candidates choose this
Candidates may confuse 'classifying' the type of document with 'extracting' text from it, assuming that identifying the label type is sufficient to retrieve the data.
✗Face DetectionWrong answer — click to see why▾
Why this is wrong here
Face detection identifies human faces in images, but the question requires extracting text (tracking numbers, addresses, names) from shipping labels, which is a text extraction task, not face detection.
★ When this WOULD be the correct answer
A question asking: 'Which Computer Vision service can be used to detect and locate human faces in an image for security surveillance?' would make Face Detection correct.
Why candidates choose this
Candidates might confuse 'detection' tasks, thinking face detection can identify any object or text, or they may not distinguish between detecting faces and extracting 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
Regression and Classification
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.
Key term
Image classification
Image classification is the process of teaching a computer to look at a picture and decide what category or label best describes the main object or scene in that picture.
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JA
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.