Image Analysis with Matlab
Description: This workshop presents principles and methods for analyzing images, including those from x-rays, photographs and tomography. The discussion will focus on using the image processing tool box in Matlab, but the concepts apply to image processing and analysis tools from other packages.
We will begin with a brief introduction to Matlab, including:
- Matlab interface components
- checking the Matlab version, loaded toolboxes and workspace
- variable types
- how to use basic functions in Matlab
- creating and running an m-file (script) file
- working with arrays.
The bulk of the time will be spent working with a variety of image manipulation techniques, such as thresholding, masking, as well as the basics of working with histograms:
- the main example will be finding the percent of porosity in the particle
- how to work with histograms
- thresholding
- mask files
- binary operations
- morphological operations (erode, dilate, open and close etc)
- discussion of extending the analysis to 3D data sets
From the Mathworks website:
“Image analysis involves processing an image into fundamental components in order to extract statistical data. Image analysis can include such tasks as finding shapes, detecting edges, removing noise, counting objects, and measuring region and image properties of an object.”
“You can perform image analysis in MATLAB® with the Image Processing Toolbox™, which provides image processing algorithms, tools, and a comprehensive environment for data analysis, visualization, and algorithm development.”
Some programming experience is recommended for this course.
Who should attend? Clients with an interest in numerical data analysis and visualization.
Obtain Matlab through Mathworks: http://www.mathworks.com/.
GNU Octave is a programming environment that is largely compatible with Matlab, but is available at no charge. Obtain GNU Octave from: https://www.gnu.org/software/octave/.