Quick Answer
The answer is Optical Character Recognition (OCR). This Azure Computer Vision capability is specifically designed for digitizing printed text from scanned books, as it extracts characters from images and converts them into machine-readable, searchable, and editable text. For the historical society’s 19th-century prints, OCR analyzes the visual patterns of letters and words, outputting a digital string that enables full-text search and editing. On the AI-900 exam, this question tests your understanding of Azure Computer Vision’s prebuilt features—OCR is the correct choice for text extraction, while other options like image tagging or object detection focus on different visual elements. A common trap is confusing OCR with the Read API, but remember: OCR is the broader capability that includes the Read API for larger documents. Memory tip: OCR stands for “Optical Character Recognition,” and you can think of it as “Old Character Reading” for historical books.
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. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. 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 historical society has scanned hundreds of books printed in the 19th century. They want to convert the scanned images into searchable, editable text. Which Azure Computer Vision capability should they use?
Optical Character Recognition (OCR)
OCR extracts printed text from images, making it searchable and editable.
Object detection
Why wrong: Object detection finds and locates objects in an image, not text.
Image classification
Why wrong: Image classification assigns a label to the whole image, it does not extract text.
Facial detection
Why wrong: Facial detection identifies human faces, not text content.
Answer choices
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 (OCR) is the Azure Computer Vision capability designed to extract printed or handwritten text from images and convert it into machine-readable, searchable, and editable text. For the historical society's scanned books, OCR can detect characters and words from the 19th-century prints and output them as digital text, enabling full-text search and editing.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
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 printed text from images, making it searchable and editable.
Related concept
Read the scenario before looking for a memorised answer.
Object detection
Why it's wrong here
Object detection finds and locates objects in an image, not text.
Image classification
Why it's wrong here
Image classification assigns a label to the whole image, it does not extract text.
Facial detection
Why it's wrong here
Facial detection identifies human faces, not text content.
Common exam traps
The trap here is that candidates may confuse OCR with general image analysis capabilities like object detection or classification, not realizing OCR is the specific service for text extraction from images.
Detailed technical explanation
Azure Computer Vision's OCR API uses deep-learning models to analyze images at the pixel level, recognizing characters through pattern matching and layout analysis. It can handle various fonts, sizes, and degraded print quality common in 19th-century books, and outputs structured JSON with bounding boxes, confidence scores, and recognized text. In practice, OCR may struggle with heavy ink bleed or faded text, requiring preprocessing like contrast adjustment or binarization to improve accuracy.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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.
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FAQ
Describe features of computer vision workloads on Azure — This question tests Describe features of computer vision workloads on Azure — Read the scenario before looking for a memorised answer..
The correct answer is: Optical Character Recognition (OCR) — Optical Character Recognition (OCR) is the Azure Computer Vision capability designed to extract printed or handwritten text from images and convert it into machine-readable, searchable, and editable text. For the historical society's scanned books, OCR can detect characters and words from the 19th-century prints and output them as digital text, enabling full-text search and editing.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Same concept, more angles
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A government agency needs to digitize thousands of handwritten application forms so that the text can be searched and processed. Which Azure Computer Vision capability should they use?
easyWhy B: The correct answer is B, Optical Character Recognition (Read API), because the agency needs to extract printed or handwritten text from images of application forms and make it searchable and processable. The Read API is specifically designed for this purpose, handling both printed and handwritten text, and is part of Azure Computer Vision's OCR capabilities.
Last reviewed: Jun 11, 2026
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