 
Course
Highlights
This three-day course shows how to perform various image processing techniques using the Image Acquisition Toolbox and Image Processing Toolbox in MATLAB environment and 'Video and Image Processing Blockset' in SIMULINK environment. The course introduces image processing fundamentals as a startup. The course explores the process of acquiring image using webcam, different types of image representations, how to enhance image characteristics, image filtering, and how to reduce the effects of noise and blurring in an image. It also introduces different methods used to extract features and objects within an image and introduction to Video and Image Processing Blockset. Implementation of basic image processing design flow from algorithm concepts to hardware simulation on field programmable gated array (FPGA) is introduced.
Course
Objectives
The aim of the course is to provide basic knowledge for participants to acquire image using the Image Acquisition Toolbox, to perform various image processing techniques using the Image Processing Toolbox and Video and Image Processing Blockset, to implement basic image processing algorithm on hardware.
Who
Must Attend
Engineer, researchers, scientists, and managers from the manufacturing, government and defense sectors who want to use or plan to use image processing, to learn the fundamental knowledge in image processing, to know how to use MATLAB and SIMULINK for image processing, or to be involved in the purchase of products that involve image processing.
Course
Benefits
Upon the completion of the course, the participants will gain a comprehensive understanding on utilizing the Image Acquisition Toolbox and Image Processing Toolbox in MATLAB environment and Video and Image Processing Blockset in SIMULINK environment to design and develop image processing algorithm for their specific applications. The participants will be able to understand the design flow for implementing image processing algorithm from algorithm concept to hardware simulation.
Prerequisites
Attended "Comprehensive MATLAB ", "Comprehensive SIMULINK" and experience with basic computer operations. Basic knowledge of signal processing and image processing concepts is strongly recommended but not a must.
Course
Outline
Introduction to Image Processing Fundamental
Objective: Learn basic image processing theory
- Overview of Image Processing
- Image Preprocessing
- Image Segmentation
- Feature Extraction
- Image Analysis
Acquiring and Viewing an Image in MATLAB
Objective: Acquire an image using the Image Acquisition Toolbox and to view the image in MATLAB
- Connecting the hardware
- Retrieving hardware information
- Creating a video input object
- Configuring the video input object
- Previewing the video stream
- Acquiring the image data
- Viewing the acquired image
Working with Images in MATLAB
Objective: Understand different image types supported in MATLAB
- Exploring image types
- Importing and exporting images in MATLAB
- Viewing the image
- Finding image characteristics
- Calculating image statistics
- Converting image formats
Image Enhancement Techniques
Objective: Enhance image characteristics by adjusting the image intensity and isolating the region of interest
- Histogram-based operations (stretching, equalization, adjustment)
- Arithmetic-based operations (addition, multiplication, subtraction, division)
- Correcting image alignment
- Cropping and resizing images
Filtering Images
Objective: Understand how block processing works and investigate the implementation of both spatial domain and frequency domain filters
- Block processing of an image
- Performing image convolution and correlation
- Designing and implementing filters
• Spatial domain filters (averaging and sharpening)
• Frequency domain filters (low-pass filter, high-pass filter, band-pass filter)
- Processing the region of interest
Image Restoration Techniques
Objective: Reduce the effects of unwanted distortions, such as noise, blurring, and background illumination
- Reducing noise from images
• Modeling noise
• Filtering noise
- Deblurring images
- Correcting background illumination
Features Extraction using Segmentation and Edge Detection
Objective: Extract image features and measurements using different segmentation and edge detection methodologies
- Isolating image features using thresholding
- Detecting edges in an image
• Edge detection functions
• Radon transform and inverse Radon transform
• Hough transform
- Performing morphological segmentation
• Creation of structuring elements
• Dilation and erosion
• Measurement of region properties
- Applying color-based image segmentation
- Isolating objects using watershed segmentation
Introduction to Video and Image Processing Blockset
Objective: Explore some features of VIP Blockset for Image Processing
- What is the VIP Blockset?
- Capabilities of the VIP Blockset
- Working with images in Simulink
• Importing and exporting images
• Color spaces conversion
• Finding image characteristics
- Image enhancement techniques
• Image intensity adjustment
•Image enhancement using arithmetic operations
• Cropping and resizing
•Morphological image segmentation
- Exercises on static image (object extraction) and dynamic image (bouncing ball)
Implementation of Basic Image Processing on Field Programmable Gated Array (FPGA)
Objective: Describe the System Generator design flow for implementing basic image processing algorithm, identify Xilinx FPGA capabilities and implement a design from algorithm concept to hardware simulation
- Introduction to System Generator
- Basic Xilinx Design
- Getting started with Xilinx System Generator: Image Filtering
Mini Projects
Objective: Apply acquired image processing knowledge on practical applications
Exercises
Objective: practice exercises, application-specific exercises, and case studies
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