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.
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
Code
Computer Science Area
A1
Computer architecture and microelectronics
A2
Computer systems, parallel and high performance computing
A3
Computer security and distributed systems
A4
Computer networks, mobile computing, and telecommunications
B1
Algorithms and systems analysis
B2
Databases, information and knowledge management
B3
Software engineering and programming languages
B4
Artificial Intelligence and machine learning
C1
Signal processing and analysis
C2
Computer vision and robotics
C3
Computer graphics and human-computer interaction
C4
Βioinformatics, medical informatics, and computational neuroscience
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.