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IMAGE PROCESSING

Degree course: 
Corso di First cycle degree in COMPUTER SCIENCE
Academic year when starting the degree: 
2016/2017
Year: 
2
Academic year in which the course will be held: 
2017/2018
Course type: 
Supplementary compulsory subjects
Credits: 
6
Period: 
First Semester
Standard lectures hours: 
56
Detail of lecture’s hours: 
Lesson (40 hours), Laboratory (16 hours)
Requirements: 

Students will be expected to be familiar with Programming.

Final Examination: 
Orale

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 as follows:
• Written text 70%
• Project 30%

Assessment: 
Voto Finale

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.

• Introduction to Digital Image Processing: historical perspective, fields of application
• Structure and functions of a digital image processing system
• Human Vision
• Image formation
• Sampling, quantization
• Image Enhancement
• Image Restoration
• Image Segmentation
• Color models: RGB, HSI
• Color image processing
• Image Compression
• Examples of fields that use image processing: Biomedical Imaging, Earth Observation, Multimedia and Web Applications

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.

Convenzionale

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.

Professors

BINAGHI ELISABETTA

Borrowers