Image Processing with MATLAB

Prerequisites

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

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Day 1 of 2
Importing and Visualizing Images

Objective: Import image or video frames into MATLAB and visualize them. Convert images to a format that is useful for analysis.

  • Importing and displaying images
  • Converting between image types
  • Exporting images
  • Importing and playing video files
Interactive Exploration of Images

Objective: Explore object details such as shape, texture, and color and create a custom image exploration tool.

  • Obtaining pixel intensity values
  • Extracting a region of interest
  • Computing pixel statistics on a region of interest
  • Measuring object sizes
  • Creating a custom interactive tool
Preprocessing Images

Objective: Perform image preprocessing operations and apply custom functions to images.

  • Adjusting image contrast
  • Reducing noise in an image
  • Using sliding neighborhood operations
  • Using block processing operations
Spatial Transformation and Image Registration

Objective: Align images to use the same scale and orientation. Compare aligned images. Create a panoramic scene by stitching 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: Perform color segmentation to extract object of similar color. Use texture analysis to detect and extract patterns in an image and classify images based on their texture.

  • Color space transformation
  • Color segmentation
  • Texture segmentation
  • Texture based image classification
Feature Extraction

Objective: Segment objects using morphological operations and perform object shape measurements.

  • Counting objects
  • Measuring shape properties
  • Using morphological operations
  • Performing watershed segmentation