AI-900 Practice Question: Describe features of computer vision workloads on Azure
A logistics company needs to automatically read handwritten addresses from package labels using cameras on a conveyor belt. The handwriting varies greatly in style, size, and orientation. Which Azure Computer Vision capability should they use?
⚠ Common exam trap
It's easy for candidates to confuse the general-purpose OCR (Read API) with Image Analysis, which can detect printed text in some cases but is not designed for handwritten or irregular text extraction.
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 specifically designed to extract text from images, including handwritten text, and is optimized for varied styles, sizes, and orientations. Unlike standard OCR, the Read API uses deep-learning models to handle unstructured documents and real-world scenarios like package labels on a conveyor belt.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Image Analysis (describing the image content)
Why it's wrong here
Image Analysis (from Azure AI Vision) enriches an image with captions, tags, and detected objects, and can identify visual attributes such as whether content is hand-drawn or a document. However, its standard operation does not perform optical character recognition (OCR); it returns the image's semantic description rather than the textual characters present in the image. As a result, it might detect an envelope or handwritten markings but cannot read the address text, so it is not suitable for this logistics requirement.
- ✓
OCR (Read API)
Why this is correct
The Read API is a specialized OCR subservice within Azure AI Vision, optimized to extract both printed and handwritten text from images and documents. It returns structured results with line-level and word-level bounding boxes, confidence scores, and recognized text, making it ideal for reading individual addresses on packages or letters. Because it explicitly supports handwriting and handles varying scripts and layouts, it is the correct Azure service for automatically reading handwritten addresses.
- ✗
Face API
Why it's wrong here
Face API is a purpose-built service for analyzing human faces: it detects face landmarks, estimates age, emotion, and other attributes, and supports facial recognition tasks. It has no optical character recognition or text extraction capability, so it cannot read or interpret any characters, whether handwritten or printed. Since the task requires reading addresses—not detecting faces—Face API is entirely unrelated and would not produce the needed output.
- ✗
Custom Vision
Why it's wrong here
Custom Vision is a model training service that lets you create custom image classifiers or object detectors by uploading labeled images and training a model to recognize specific classes of objects. Its primary purpose is to detect predefined categories (e.g., 'defective part' or 'cat'), not to extract arbitrary textual content from images. To read handwriting, you would need to train a model for each character and still handle variability poorly, whereas Azure provides the Read API for OCR, making Custom Vision an inefficient and unsuitable choice here.
Go deeper
Related to this question
Learn chapter
Machine Learning Core Concepts
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
OCR
Optical Character Recognition is technology that converts images of text, like scanned documents or photos, into machine-readable text data.
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