Master the essential preprocessing techniques that transform raw visual data into model-ready inputs for computer vision systems. This course empowers you to systematically prepare image data through normalization and color-space conversions, then advance to extracting meaningful motion information from video sequences. You'll apply pixel value normalization, execute color transformations between RGB, grayscale, HSV, and BGR formats, then implement optical flow algorithms and frame differencing to capture temporal dynamics. By completing this course, you'll be able to:
Process Images, Create Captioning AI Models
Process Images, Create Captioning AI Models
This course is part of Vision & Audio AI Systems Specialization
Instructor: Hurix Digital
Included with
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
2 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Image preprocessing using normalization and color-space conversion ensures stable training and consistent model performance.
Optical flow and frame differencing complement motion analysis, helping systems capture scene dynamics over time.
Preprocessing is essential for vision tasks, directly affecting model convergence, stability, and real-world results
Motion feature extraction links static images with dynamic understanding for recognition, tracking, and navigation.
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Recently updated!
March 2026
Assessments
3 assignments
Taught in English
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This course is part of the Vision & Audio AI Systems Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 2 modules in this course
Learners will master systematic image preprocessing techniques including normalization and color-space conversions to prepare raw visual data for computer vision applications.
What's included
3 videos1 reading1 assignment1 ungraded lab
Learners will master optical flow and frame differencing techniques to extract temporal motion features from video sequences for computer vision applications.
What's included
2 videos1 reading2 assignments
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