Course Description
This course introduces fundamental and advanced methods in machine and computer vision with an emphasis on engineering applications. Topics include image formation, enhancement, segmentation, 3D vision, and deep learning approaches for various tasks. Students will gain hands-on experience developing vision pipelines using Python and may optionally implement solutions in Matlab.
Athena Title
Mach & Comp Vision for ENGR
Semester Course Offered
Offered fall and spring
Grading System
A - F (Traditional)
Student learning Outcomes
- By the end of this course, students will be able to explain foundational principles of imaging, sensing, and vision system operation.
- By the end of this course, students will be able to apply core image processing, computer vision, and machine/deep learning techniques to analyze visual data.
- By the end of this course, students will be able to develop and implement vision workflows using modern computational tools (e.g., Python and associated libraries).
- By the end of this course, students will be able to evaluate and communicate the effectiveness of vision-based engineering solutions through technical analysis and presentation.
Topical Outline
- Course Overview & Colab Orientation (Self-Guided)
- Image Formation & Representation, Image Quality & Enhancement
- Binary & Grayscale Image Processing, Color & Frequency Domain Processing
- Image Segmentation (Traditional Approaches)
- 3D Vision & Optical Metrology
- Introduction to Machine & Deep Learning for Vision
- Deep Learning for Classification & Object Detection
- Deep Learning for Segmentation
- Advanced Topics in Vision
- Vision Applications in Engineering
