MATLAB & Simulink

IMAGE PROCESSING AND COMPUTER VISION

Essentials of Image Processing with MATLAB

This two-day course provides hands-on experience with performing image analysis. Examples and exercises demonstrate the use of appropriate MATLAB® and Image Processing Toolbox™ functionality throughout the analysis process.
Topics include:

  • Importing and exporting images

  • Analyzing images interactively

  • Removing noise

  • Aligning images and creating a panoramic scene

  • Detecting edges, lines, and circles in an image

  • Segmenting objects based on their color and texture

  • Modifying objects' shape using morphological operations

  • Performing batch analysis over sets of images

  • Measuring shape properties

Prerequisites

MATLAB Fundamentals or equivalent experience using MATLAB. Basic knowledge of image processing concepts is strongly recommended.​

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Course Outline

Day 1 of 2

Importing and Visualizing Images

 

Objective: Import images into MATLAB and visualize them. Convert the images to a format that is useful for subsequent analysis steps.

  • Importing and displaying images

  • Converting between image types

  • Exporting images

 

Interactive Exploration of Images

 

Objective: Interactively explore object details such as size and color to find start values for subsequent image processing steps. To apply the steps repeatedly, you can create custom image exploration tools from the interactive modules.

  • Obtaining pixel intensity values

  • Extracting a region of interest (ROI)

  • Computing pixel statistics on a region of interest

  • Measuring object sizes

  • Creating a custom interactive tool

 

Preprocessing Images

 

Objective: Preprocess images by filtering, and using contrast adjustment to simplify or allow for image analysis steps. 

  • Adjusting image contrast

  • Reducing noise in an image by filtering

  • Handling inhomogenous background

  • Applying custom functions block by block

 

Spatial Transformation and Image Registration

 

Objective: Compare images with different scaling and orientation by aligning them. Use the same techniques for creating  panoramic images.

  • Geometric transformations

  • Image registration using point mapping

  • Creating a panoramic scene

Day 2 of 2

Edge and Line Detection

 

Objective: Segment edges of objects and extract boundary pixel locations. Detect lines and circles in an image.

  • Segmenting object edges

  • Detecting straight lines

  • Performing batch analysis over sets of images

  • Detecting circular objects

 

Color and Texture Segmentation

 

Objective: Segment objects based on color or texture. Use texture features for image classification.

  • Color space transformation

  • Color segmentation

  • Texture segmentation

  • Texture-based image classification

 

Feature Extraction

 

Objective: Analyze and modify the object's shape to improve segmentation results. Count the detected objects and calculate object features like area or centroids.

  • Counting objects

  • Measuring shape properties

  • Using morphological operations

  • Performing watershed segmentation

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