MATLAB & Simulink


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

  • Detecting, extracting, and matching image features

  • Removing noise

  • Aligning images

  • 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


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


Upcoming Program

Techsource Systems is
Mathworks Sole and Authorised Distributor and Training Partner

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


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. 

  • Geometric transformations

  • Image registration using point mapping

  • Image registration using phase correlation

Automating Image Registration with Image Features

Objective: Detect, extract, and match sets of image features to automate image registration.

  • Detecting and extracting features

  • Matching features

  • Estimating geometric transformations between images

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