MTAT.03.260 Pattern Recognition and Image Analysis
MTAT.03.260 Pilditöötluse ja kujundituvastuse alused
- Seminars: On Tuesdays at 14:15-15:45 J. Liivi 2 - 403
- Office hours: Mondays Liivi 2-326. Please arrange exact details of the meeting by email.
- Questions: email@example.com
- The first seminar starts on 14:15 on 8th February
- The course is based on three standard handbooks:
- Rafael C. Gonzalez, Richard E. Woods, Digital Image Processing.
- Rafael C. Gonzalez, Richard E. Woods, Steven L. Eddins, Digital Image Processing using MATLAB.
- William K. Pratt, Digital Image Processing.
- Lectures and seminar sessions are held in English or in Estonian depending on circumstances.
- Final reports should be written preferably in English.
What and Why
The course aims to give a overview of basic image processing and analysis techniques starting from data representation and ending with basic shape detection methods. The main motivation behind the course is to familiarize students studying bioinformatic and robotics with the tools needed to process digital images. For instance, calibrate the camera feed of an optical sensor so that specific objects can be found and traced, i.e., to implement rudimentary computer vision needed to solve simple tasks in robotics. In bioinformatics, the main emphasis is currently analysis of still images. One needs to detect cell borders and organelles, differentiate between different cell types, convert and interpret color intensities of specific dye-s used to highlight presence of specific proteins.
The course covers basics of image processing. We start form image representation: discuss various color schemes (RGB, CMYK, HCI, HCL) and methods for filtering out specific color channels. After that we give an overview of common spatial filers: linear high and lowpass filters, nonlinear filters for edge detection. Next, we cover briefly properties of Fourier transformation and some basic filtering techniques used in frequency domain. Then we continue with morphological processing of binary, monochrome and color images.
There are no formal prerequisites to the seminar. However, basic knowledge in programming, basic math and linear algebra is advisable. Also, one needs reasonable English skills to complete the course report. If the formal requirements of the ÕIS do not permit registration then write me an email or talk with me. After that we decide whether to enroll you or not.
To pass the course
- You have to give at least one presentation about the topics covered in this course.
- You must write an illustrative demo application for covering the techniques you present. You do not have to implement the algorithms by yourself. It is sufficient if you use packages of R or some other computing software.
- You must actively participate in most seminars or otherwise you do not pass the seminar. Namely, student gets grade F if he or she misses 3 or more seminars. In reasonable circumstances, it is possible to compensate missed seminars by extra work. Details are determined by individual agreements with the lecturer.
- You must do a project work. The project work will be graded in the scale from A to F and it will form the basic grade for the course.
- The requirements for the project work are standard: they must cover the main research problem and methods so that they would be understandable for the fellow students. The description of experiments should be detailed enough so that it is repeatable by others and your own contribution is clearly visible. Results should be presented together with clear interpretation.
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