IMAGE PROCESSING
- Overview
- Assessment methods
- Learning objectives
- Contents
- Bibliography
- Delivery method
- Teaching methods
- Contacts/Info
Students will be expected to be familiar with Programming.
The evaluation consists in a written examination lasting 2 hours and the development of a project. The test of the written examination consists of 3 questions in general, some entirely 7theory, some including numerical exercises.
Projects typically involve image processing tasks similar to those presented and developed in laboratory
The separate assessment elements contribute towards the final mark according to the following rule:
• Written text 70%
• Project 30%
Course Objectives and Expected Outcomes
This course introduces the fundamentals of digital image processing. It emphasizes both general principles of image processing and specific applications in several domains including Earth Observation, Biomedical Imaging, Multimedia and Web Applications
Upon completion of this course, the students will be able to:
1)Describe the basic theory and concepts of the following areas:
• Image formation and Acquisition
• Image Enhancement and Segmentation
• Color Images
• Compression
2) Apply techniques of
Image enhancement with local and punctual operators
Image Segmentation for contour and region extraction
noise reduction
Emphasis is on the general principles and methods of image processing. Students will implement and investigate the behavior of image processing algorithms with the help of e-learning tools and processing systems such as HIPR2 and Image J.
It is also expected that communication skill and autonomous assessments will be developed through open discussions on topic covered and experimental results
The acquisition of knowledge and expected skill is developed along the entire course that includes the topics listed below.
1)Fundamentals (8 h)
-Introduction to Digital Image Processing: historical perspective, fields of application
- Structure and functions of a digital image processing system
-Human Vision and Image formation
- Sampling, quantization
2)Image Enhancement (15 h)
3) Image Segmentation (8)
4) Color models: RGB, HSI and Color image processing (3)
5)Image Compression 2)
6)Examples of fields that use image processing: Biomedical Imaging, Earth Observation, Multimedia and Web Applications (4h)
7) Overwiew of e-learning resources and experiments with ImageJ (16)
Textbook: C. Gonzalez, R.E. Woods, Digital Image Processing, Addison Wesley , 1992
Additional readings, including slides, selected papers from the literature and links to on line demo will be posted periodically on the class website.
Course Format
Lectures (40 hours); Laboratory (16 hours)
Laboratory activities includes the use of e-learning tools and Image Processing tools such as ImageJ, under the supervision of the teacher.
Office hours
Office hours is agreed by e-mail.
Borrowed from
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