The course covers basic concepts and fundamental methodologies of Image Analysis, including the following themes: edge detection, histogram-based segmentation, segmentation by region splitting and merging, superpixels, region growing, Markov random field models for segmentation, segmentation using graph cuts, mean-shift algorithm, active contours, level sets, morphological image processing, watershed segmentation, boundary extraction, boundary description, image region description, texture description, corner detection, keypoint extraction, image classification.
Learning Outcomes
Knowledge: Having attended and succeeded in the course, the student is able to describe and understand the basic principles and techniques of image analysis. Understanding: Having attended and succeeded in the course, the student has achieved an in-depth understanding of the mechanisms for solving various problems related to image analysis. Application: Having attended and succeeded in the course, the student is able to use existing knowledge and methodologies to solve problems related to image analysis. Analysis: Having attended and succeeded in the course, the student is able to critically examine specific image analysis problems and perceive them as a composition of a series of subproblems. Synthesis: Having attended and succeeded in the course, the student is able to combine various tools and methodologies to solve complex image analysis problems. Evaluation: Having attended and succeeded in the course, the student is able to measure/quantitatively assess the quality of solutions to image analysis problems and compare these solutions with other existing ones.
Student Performance Evaluation
Specific details on grading can be found on the course’ s website
The courses of the Computer Science Department are designated with the letters "CS" followed by three decimal digits. The first digit denotes the year of study during which students are expected to enroll in the course; the second digit denotes the area of computer science to which the course belongs.
First Digit
Advised Year of Enrollment
1,2,3,4
First, Second, Third and Fourth year
5,6
Graduate courses
7,8,9
Specialized topics
Second Digit
Computer Science Area
0
Introductory - General
1
Background (Mathematics, Physics)
2
Hardware Systems
3
Networks and Telecommunication
4,5
Software Systems
6
Information Systems
7
Computer Vision and Robotics
8
Algorithms and Theory of Computation
9
Special Projects
The following pages contain tables (one for each course category) summarizing courses offered by the undergraduate studies program of the Computer Science Department at the University of Crete. Courses with code-names beginning with "MATH" or "PHYS" are taught by the Mathematics Department and Physics Department respectively at the University of Crete.