Description
Information
| Instructors: | Prof. Ioannis Kakadiaris (COSC 6397) Prof. Shishir Shah (COSC 4393) |
| Prerequisites: | You are expected to know basics of linear algebra, linear systems, calculus, and probability/statistics. Homework assignments and course projects will require knowledge of C/C++/Java. |
| Outline: | The objective of this course is to introduce the essential concepts of digital image processing from an operational perspective with some exposure to theory. Aspects of image acquisition, processing, practical applications, and elementary image analysis algorithms will be covered. This course will make digital image processing accessible to computer scientists and engineers that are currently unfamiliar with the topic. We will be programming in C/C++/Java and/or MATLAB for numerous visual examples in the form of actual digital image processing results and homework assignments. |
| Tentative Topics: | Digital Image Acquisition, Binary Image Processing, Histogram and Point Operations, Discrete Fourier Transform, Sampling Theorem, Linear Filtering, Enhancement, and Restoration, Nonlinear Image Filtering, Digital Image Coding and Compression |
| Tentative Grading: | Homework 30%, Midterm Exam 30%, Term Project 30%, Final Report 10% |
| Recommended Text: | Digital Image Processing, 2nd Edition, R. C. Gonzales and R. E. Woods, Prentice Hall, 2002. |
| Supplement: | Digital Image Processing, K. R. Castleman, Prentice Hall, 1996. |
Course Objective
- Introduce essential concepts of Digital Image Processing
- Acquisition
- Display
- Processing
- Practical Applications and Implementation
- Elementary Image Analysis
- Make digital image processing accessible to engineers and computer scientists
- Present numerous examples to illustrate the use of image processing and the material taught in class
- Create an interactive teaching environment
- Ask questions
- Comment on level of instruction and material
- Comment on speed of delivery
What will you know at the end of this course?
- Understanding of theoretical as well as practical issues of basic digital image acquisition and processing
- The ability to apply digital image processing principles for emerging applications in inspection, remote sensing, microscopy, surveillance, robotic assembly, etc.
- The ability to perform various operations on images, such as, filtering, enhancement, restoration, edge detection, segmentation, template matching, etc.
- Understanding of current research initiatives within the image processing and analysis community
- Ability to complete an independent practical project and carryon further research
- Preparation for deeper understanding in image processing and related topics in image analysis, computer vision, pattern recognition, etc.