Daniel B. Rowe, Ph.D.
MATH 4770/MSSC 5770: Statistical Machine Vision
There is not a required book. All material will be presented via lecture.
Course Syllabus Summer 2025
Syllabus
,
Schedule
Flyer
Lecture Topics
Course Slides
Lecture 00:
Syllabus
Lecture 01:
Matlab
(
Car Data
,
Father Marquette
) Lecture 02:
Within Image Processing
(
Kernel Movie
,
Smoothing
,
Edges
,
Gradient
) Lecture 03:
Image Filter Design
(
Gaussian
,
Binomial
,
Test Image
,
Test Image
) Lecture 04:
Statistical Implications
(
My Convolution
,
Colormap Pos-Neg
) Lecture 05:
The Correlation Coefficient
Lecture 06:
Pixel Statistics & Template Matching
(
My Correlation
,
Colormap Pos
) Lecture 07:
Through Image Processing
(
Cat Video
) Lecture 08:
The Discrete Fourier Transform
(
FMRI k-space
) Lecture 09:
Convolution via the DFT
Lecture 10:
Fast Object Tracking
(
Shelby Video
,
Shelby Template
,
Tracking on Correlation
,
Tracking on Image
) Lecture 11:
Peaks, Valleys, and Ridges
Lecture 12:
Machine Vision Summary
All topics and assignments will have a computational aspect using Matlab.
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