Course Description
2D- and 3D-vision systems for identification, measurement, and quality control. Electromagnetic spectrum, illumination design, imaging sensor election, vision system calibration. Implementation of image processing algorithms for object recognition and classification, stereo vision.
Additional Requirements for Graduate Students:
Graduate students will be required to perform more advanced
projects which could be related to their research areas.
Athena Title
Applied Machine Vision
Undergraduate Prerequisite
Permission of department
Graduate Prerequisite
Permission of department
Semester Course Offered
Offered spring
Grading System
A - F (Traditional)
Course Objectives
Upon successful completion of this course, the student will be able to: 1. Have a basic understanding of spectrometry and machine vision technologies 2. Analyze a problem description and derive a solution suitable to 2D and 3D machine vision techniques 3. Apply image processing techniques for extracting features from an image 4. Understand the components of a machine vision system (2D and 3D).
Topical Outline
Electromagnetic radiation spectrum; light interaction with matter: reflectance, transmission, absorbance; radiation detection: linear and array detectors, spectrometers and cameras; illuminant characteristics and spectra: image quality, spectral filters; vision system calibration: color spaces, geometric calibration; introductory image processing: segmentation, edge detection, noise filtering; stereo vision: multi-view and structured light approaches.