Learn about optical character recognition (OCR) and how it enables extracting text from handwritten documents, a key concept covered in the Microsoft AI-900 Azure AI Fundamentals certification exam.
Table of Contents
Question
What extracts text from handwritten documents?
A. Image classification
B. Object detection
C. Facial recognition
D. Optical character recognition (OCR)
Answer
D. Optical character recognition (OCR)
Explanation
Optical character recognition (OCR) is the AI technology that extracts text from handwritten documents. OCR works by analyzing images of handwritten or printed text and using machine learning algorithms to identify and convert the characters into machine-readable text.
The key steps in the OCR process are:
- Pre-processing the image to enhance quality and remove noise
- Segmenting the image into lines and individual characters
- Recognizing each character using trained ML models
- Post-processing to improve accuracy and format the output text
So in summary, OCR enables digitizing handwritten documents by automatically extracting the text content into an editable, searchable format. The other options like image classification, object detection, and facial recognition have different purposes and do not apply to extracting text from documents.
Understanding OCR is important for the Azure AI-900 exam as it is a fundamental AI technology with many practical business applications. I hope this explanation helps clarify the concept for you. Let me know if you have any other questions!
Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Microsoft Azure AI Fundamentals AI-900 exam and earn Microsoft Azure AI Fundamentals AI-900 certification.