MATLAB PROGRAMMING

MATLAB Programming

Introduction

Obtain a quick overview of The Math Works and MATLAB

Discuss course set-up

Evolution of the language

Features of Mat lab

Working with the MATLAB User Interface

Command window

Command History

Workspace

Reading and writing data

Variables and Expressions

Entering commands

Creating variables

Getting help

Accessing and modifying values in variables

Operators

Operators classification

Arithmetic operators

Relational operators

Logical operators

Assignment operator

Semicolon operator

Colon operator

Typecasting operator

Flow Control

Simple if

If - else

Else if

Nested if

Switch

For loop

While loop

Writing Functions

Creating functions

Calling functions

Sub functions

Data Types

MATLAB? data types

Integers

Structures

Function handles

Analysis and Visualization with Vectors

Calculations with vectors

Plotting vectors

Basic plot options

Annotating plots

Analysis and Visualization with Matrices

Size and dimensionality

Calculations with matrices

Multidimensional arrays

Graphics

2Dimensional plots

3Dimensional plots

Contour plots

File I/O

Opening and closing files

Reading and writing text files

Reading and writing binary files

Graphical User Interfaces

GUIDE introduction

Designing the GUI

Programming the GUI

MATLAB Image Processing Training

We provide 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 lines and circles in an image

Segmenting object edges

Segmenting objects based on their color and texture

Performing batch analysis over sets of images

Segmenting objects based on their shape using morphological operations

Measuring shape properties

Course Objective

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

MATLAB Image Processing Training

We shows how to analyze signals and design signal processing systems using MATLAB, Signal Processing Toolbox^?, and DSP System Toolbox.

Topics include:

Creating and analyzing signals

Performing spectral analysis

Designing and analyzing filters

Designing multi-rate filters

Designing adaptive filters

Course Objective: Signals in MATLAB

Objective: Generate sampled and synthesized signals from the command line and visualize them. Create noise signals for a given specification. Perform signal processing operations like re-sampling, modulation, and correlation.

Creating discrete signals

Sampling and re-sampling

Visualizing signals

Modeling noise

Performing re-sampling, modulation, and correlation

Generating streaming signals

Spectral Analysis

Objective: Understand different spectral analysis techniques and the use of windowing and zero padding. Become familiar with the spectral analysis tools in MATLAB and explore nonparametric (direct) and parametric (model-based) techniques of spectral analysis.

Discrete Fourier transform

Windowing and zero padding

Power spectral density estimation

Time-varying spectra

Using a spectrum analyzer in MATLAB

Linear Time Invariant Systems

Objective: Represent linear time-invariant (LTI) systems in MATLAB and compute and visualize different characterizations of LTI systems.

LTI system representations

z-transform

Frequency and impulse response

Visualizing filter properties

Applying filters to finite and streaming signals