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

  • Removing noise

  • Aligning images

  • Detecting, extracting, and matching image features

  • Detecting edges, lines, and circles in an image

  • Segmenting objects based on their color and texture

  • Modifying objects' shape using morphological operations

  • Measuring shape properties

  • Performing batch analysis over sets of image

Who Should Attend

Engineers, researchers, scientist who are working to enhance, segment and extract features from images 

Course Prerequisites

MATLAB Fundamentals

Course Benefits

Upon the completion of the course, the participants will be able to

- explore images - enhance images

- perform image registration - segment regions in image

- extract features from image 



Upcoming Program

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Techsource Systems is
Mathworks Sole and Authorised Distributor and Training Partner

Course Outline

Day 1 of 2

Importing and Visualizing Images


Objective: Import and display different types of images. Convert between image data types and formats to facilitate subsequent analysis steps. 

  • Importing and displaying images

  • Converting between image types

  • Visualizing results of processing

  • Exporting images


Preprocessing Images


Objective: Enhance images to simplify analysis and processing. Use common preprocessing techniques such as histogram-based contrast adjustment and noise filtering to improve segmentation.  

  • Improving image contrast 

  • Reducing noise in an image

  • Equalizing inhomogeneous background 

  • Processing images block by block 


Spatial Transformation and Image Registration


Objective: Compare two images with different scales and orientations by geometrically aligning them. 

  • Applying geometric transformations to images 

  • Aligning images using point mapping 

  • Automating intensity-based registration 

Automating Image Registration with Image Features

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

  • Detecting and extracting features

  • Matching features to estimate geometric transformation between two images 

Day 2 of 2

Edge and Line Detection


Objective:  Detect edges of objects and extract boundary pixel locations. Detect objects by their shape. 

  • Detecting object edges 

  • Segmenting objects by finding straight lines and circles 

  • Performing batch analysis over sets of images 


Color and Texture Segmentation


Objective: Segment objects based on color and texture. Use statistical measures such as contrast and correlation to characterize texture features for image classification. 

  • Transforming between image color spaces 

  • Segmenting objects based on a color difference metric 

  • Using non-linear filters to segment objects based on texture 

  • Analyzing image texture using statistical measures 

  • Measuring texture similarity 


Feature Extraction


Objective: Analyze and modify objects' shape to improve segmentation results. Count and label the objects detected in an image. Extract object properties like area or centroid. 

  • Counting objects from a segmentation 

  • Measuring shape properties 

  • Using morphological operations to refine segmentation results 

  • Performing watershed segmentation to improve object separation