MATLAB & Simulink
IMAGE PROCESSING AND COMPUTER VISION
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:
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Importing and exporting images
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Removing noise
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Aligning images
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Detecting, extracting, and matching image features
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Detecting edges, lines, and circles in an image
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Segmenting objects based on their color and texture
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Modifying objects' shape using morphological operations
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Measuring shape properties
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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
Partners

Upcoming Program
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Please keep me posted on the next schedule
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Please contact me to arrange customized/ in-house training

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.
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Importing and displaying images
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Converting between image types
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Visualizing results of processing
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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.
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Improving image contrast
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Reducing noise in an image
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Equalizing inhomogeneous background
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Processing images block by block
Spatial Transformation and Image Registration
Objective: Compare two images with different scales and orientations by geometrically aligning them.
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Applying geometric transformations to images
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Aligning images using point mapping
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Automating intensity-based registration
Automating Image Registration with Image Features
Objective: Detect, extract, and match image features to automate image registration.
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Detecting and extracting features
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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.
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Detecting object edges
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Segmenting objects by finding straight lines and circles
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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.
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Transforming between image color spaces
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Segmenting objects based on a color difference metric
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Using non-linear filters to segment objects based on texture
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Analyzing image texture using statistical measures
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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.
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Counting objects from a segmentation
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Measuring shape properties
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Using morphological operations to refine segmentation results
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Performing watershed segmentation to improve object separation