Automating Image Processing
This course is part of multiple programs. Learn more.
This advanced course teaches automation techniques for processing large image and video datasets. Students learn batch processing, video analysis, and automated result verification. The curriculum includes practical projects in traffic monitoring, with emphasis on car detection in noisy video data and statistical analysis of results.
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What you'll learn
Process large image datasets efficiently
Analyze video files systematically
Automate result verification
Detect objects in noisy videos
Implement batch processing workflows
Perform statistical analysis
Skills you'll gain
This course includes:
41 Minutes PreRecorded video
8 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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There are 4 modules in this course
This comprehensive course focuses on automating image processing workflows for large-scale applications. Through four modules, students learn batch processing techniques, video file handling, and automated analysis methods. The curriculum culminates in a practical project detecting and analyzing vehicles in traffic video footage.
Processing Batches of Images
Module 1 · 3 Hours to complete
Working with Video Files
Module 2 · 1 Hours to complete
Analyzing Results
Module 3 · 54 Minutes to complete
Final Project: Detecting Cars in a Noisy Video
Module 4 · 7 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: MathWorks Computer Vision Engineer Professional Certificate, Image Processing for Engineering and Science Specialization
Instructors
Manager Online Courses
Brandon Armstrong is a Principal Online Content Developer at MathWorks. He earned a Ph.D. in physics from the University of California at Santa Barbara in 2010.
Online Course Developer at MathWorks
Amanda Wang is an Online Course Developer at MathWorks, specializing in creating educational content related to MATLAB and its applications in computer vision and deep learning. She holds dual Bachelor's degrees in Mathematics with Computer Science and Business Analytics from the Massachusetts Institute of Technology (MIT), which she completed in 2020. Currently, Amanda is pursuing a Master’s degree in Computer Science from the University of Illinois Urbana-Champaign.
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Frequently asked questions
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