- Undergraduate
Bachelor's Degrees
Bachelor of ArtsBachelor of EngineeringDual-Degree ProgramUndergraduate AdmissionsUndergraduate Experience
- Graduate
Graduate Experience
- Research
- Entrepreneurship
- Community
- About
-
Search
ENGG 417 - Machine Vision
Description
This graduate-level course combines image processing, machine learning, and hardware design concepts, with a focus on implementing machine vision systems on low-level hardware. In this course, you will leverage industry-standard digital design tools to evaluate and compare the performance of high-speed vision algorithms implemented on an SoC (system on a chip), and you will explore optimization techniques to perform real-time video processing. This class will expand on fundamental computer vision algorithms, such as image segmentation, feature extraction, motion tracking, object detection, and filtering, emphasizing the hardware implementation of real-world machine vision applications. Throughout the course, you will explore vision concepts using both software and hardware, and you will apply this knowledge to build your own real-time video processing system on the Xilinx Zynq SoC. You will work with your peers to complete weekly lab assignments, which will culminate in a final project.Notes
This course is open only to students enrolled in the online MEng in Computer Engineering program. This course cannot be used to satisfy any AB, BE, MEM, MS, PhD, or residential MEng degree requirements.Offered
Term: Summer 2025
Time: Online students only
Location: –
Instructors:
Kendall R Farnham