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MATLAB Academy

Image Processing with MATLAB

MathWorks via MATLAB Academy


  • Course Overview: Familiarize yourself with the course.
  • Working with Image Data: Import, visualize, and extract information from different image types and image data types.
  • Preprocessing: Preprocess images to improve algorithms: enhancing contrast, noise removal techniques, block processing, and quality metrics.
  • Segmenting Based on Color: Use color spaces, regions of interest, and the Color Thresholder app to segment images based on color.
  • Segmenting Based on Texture: Use range, entropy, and standard deviation filters to separate regions based on texture.
  • Improving Segmentations: Refine your segmentation with morphological operations. Automate segmentation from a seed mask using iterative techniques.
  • Finding and Analyzing Objects: Separate overlapping objects in your segmentation. Label objects and measure their properties, such as area and perimeter.
  • Detecting Edges and Shapes: Detect edges of objects and identify lines and circles in an image.
  • Batch Processing: Process large numbers of files using the Image Batch Processor app and image datastores.
  • Aligning Images with Image Registration: Register images using phase correlation, control points, and feature matching.
  • Conclusion: Learn next steps and give feedback on the course.


  • Course Overview
  • Introduction
  • Extracting Metadata from Image Files
  • Representing Different Image Types
  • Converting Image Data Types
  • Working with Binary Images
  • Summary
  • Introduction
  • Adjusting Contrast
  • Block Processing
  • Filtering Noise
  • Quality Metrics
  • Background Subtraction
  • Summary
  • Introduction
  • Thresholding by Color
  • Representing Images in Different Color Spaces
  • Using the Color Thresholder App
  • Segmenting Based on a Region of Interest
  • Summary
  • Introduction
  • Texture Filters
  • Summary
  • Introduction
  • Cleaning Binary Masks
  • Growing Segmentations with Active Contours
  • Growing Segmentations with the Fast Marching Method
  • Using the Image Segmenter App
  • Summary
  • Introduction
  • Working with Connected Components of a Mask
  • Separating Overlapping Objects with Watershed Segmentation
  • Measuring Shape Properties
  • Summary
  • Introduction
  • Detecting Edges
  • Detecting Circles
  • Detecting Lines
  • Summary
  • Introduction
  • Using the Image Batch Processor App
  • Batch Processing with Image Datastores
  • Summary
  • Introduction
  • Applying Geometric Transformations
  • Estimating a Geometric Transformation
  • Mapping Control Points
  • Matching Image Features
  • Summary
  • Additional Resources
  • Survey

Taught by

K. Grace Kennedy


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