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. A key principle to apply: oCR extracts text from images, including printed and handwritten forms.. 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 logistics company receives thousands of handwritten shipping labels daily. They need an automated solution to extract the destination address, sender name, and package weight from these labels. Which prebuilt Azure Computer Vision capability should they use?
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)
Option A is correct because Azure Computer Vision's Optical Character Recognition (OCR) API is specifically designed to extract printed or handwritten text from images. In this scenario, the handwritten shipping labels contain textual data (destination address, sender name, package weight), and OCR can read and digitize that text for automated processing. The other options address different visual tasks—object detection, classification, or facial recognition—none of which extract text content.
Key principle: OCR extracts text from images, including printed and handwritten forms.
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
OCR extracts text (including handwriting) from images, perfect for reading shipping labels.
Related concept
OCR extracts text from images, including printed and handwritten forms.
✗
Object detection
Why it's wrong here
Object detection identifies and locates objects in images, not for reading text.
✗
Image classification
Why it's wrong here
Image classification assigns a label to the entire image, not for extracting text.
✗
Facial recognition
Why it's wrong here
Facial recognition identifies or verifies individuals from their faces, irrelevant for text extraction.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse OCR with object detection, thinking that 'extracting' information from an image is the same as identifying objects, but OCR is the only service that reads text characters from images.
Detailed technical explanation
How to think about this question
Azure Computer Vision OCR uses deep-learning models trained on millions of text samples, supporting both printed and handwritten text extraction. It returns bounding boxes, text lines, and confidence scores for each recognized word, enabling downstream parsing of structured fields like addresses. In real-world logistics, OCR must handle varied handwriting styles, smudges, and label orientations, which the API manages through preprocessing and multi-language support.
KKey Concepts to Remember
OCR extracts text from images, including printed and handwritten forms.
Azure Computer Vision's OCR supports multiple languages and handwriting styles.
OCR converts visual text into machine-readable data.
It is crucial for digitizing documents and automating data entry from images.
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
OCR extracts text from images, including printed and handwritten forms.
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.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this AI-900 question in full detail.
Review oCR extracts text from images, including printed and handwritten forms., then practise related AI-900 questions on the same topic to reinforce the concept.
Describe features of computer vision workloads on Azure — This question tests Describe features of computer vision workloads on Azure — OCR extracts text from images, including printed and handwritten forms..
What is the correct answer to this question?
The correct answer is: Optical Character Recognition (OCR) — Option A is correct because Azure Computer Vision's Optical Character Recognition (OCR) API is specifically designed to extract printed or handwritten text from images. In this scenario, the handwritten shipping labels contain textual data (destination address, sender name, package weight), and OCR can read and digitize that text for automated processing. The other options address different visual tasks—object detection, classification, or facial recognition—none of which extract text content.
What should I do if I get this AI-900 question wrong?
Review oCR extracts text from images, including printed and handwritten forms., then practise related AI-900 questions on the same topic to reinforce the concept.
What is the key concept behind this question?
OCR extracts text from images, including printed and handwritten forms.
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Question Discussion
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