AI-102 Implement computer vision solutions Practice Question
A company uses Azure AI Vision to analyze product images in an e-commerce application. The solution uses the Analyze Image API with OCR. Recently, the OCR accuracy has decreased for images with handwritten text on product labels. What should the team do to improve accuracy?
⚠ Common exam trap
It's easy for candidates to assume all OCR features in Azure AI Vision are equivalent, but the Read API is a separate, more advanced service specifically designed for handwritten and complex text extraction, while the Analyze Image API's OCR is a legacy feature for printed text only.
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
✓
Switch to the Read API for OCR.
The Read API (part of Azure AI Vision) is specifically optimized for extracting text from images, including handwritten text, and provides higher accuracy for OCR scenarios compared to the general-purpose Analyze Image API. The Analyze Image API's OCR feature is designed for printed text and does not handle handwritten content as effectively. By switching to the Read API, the team leverages a dedicated OCR engine that supports both printed and handwritten text, improving accuracy for product labels.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Enable OCR in the Analyze Image API configuration.
Why it's wrong here
OCR is already enabled; the API itself is less accurate for handwriting.
- ✗
Use Azure AI Document Intelligence prebuilt receipt model.
Why it's wrong here
This is for structured documents, not general images.
- ✓
Switch to the Read API for OCR.
Why this is correct
The Read API is better for handwritten text.
- ✗
Retrain the OCR model with additional handwritten samples.
Why it's wrong here
Prebuilt models cannot be retrained.
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