e-course on Computer Vision and Image Processing

Short e-course on Computer Vision and Image Processing, 
24-25th February 2021

Dear Computer Vision/Image Processing engineers, scientists and enthusiasts,


you are welcomed to register in this short e-course on "Computer
Vision and Image Processing", 24-25th February 2021.

It will take place as a two-day e-course (due to COVID-19
circumstances), hosted by the Aristotle University of Thessaloniki
(AUTH), Thessaloniki, Greece, providing a series of live lectures
delivered through a tele-education platform. They will be complemented
with on-line video recorded lectures and lecture pdfs, to facilitate
international participants having time difference issues and to enable
you to study at own pace.  You can also self-assess your knowledge, by
filling appropriate questionnaires (one per lecture). You will be
provided programming exercises to improve your programming skills.

It is part of the very successful CVML short course series that took
place in the last three years.

Course description "Computer Vision and Image Processing"

The short e-course consists of 16 1-hour live lectures organized in two Parts (1 Part per day):

Part A (8 hours) provide an in-depth presentation of Image Processing
theory and its application in the above-mentioned diverse
domains. First, an Introduction to Image Processing and Computer
Vision will be offered to clarify concepts in a precise and
mathematical way. Image formation and its issues (e.g., image noise,
deformations) will then be detailed, whether based on visible light or
on other modalities (e.g., Xrays, Ultrasound). Image sampling will
provide the necessary background to understand the potential and
limitations of digital images.  2D Signals and Systems will provide
the theoretical and algorithmic tools for most image processing
operations. Then notions related to Image transforms will be
clarified, together with their applications in image/video analysis
and compression.  Fast 2D convolution algorithms will provide
efficient implementation of most image processing operations. Image
perception will overview the Human Visual System and its impact on
image quality and image processing system design
specifications. Finally, Image filtering will provide tools to reduce
noise and enhance image quality, e.g., to increase contrast, perform
image zooming or printing.

Part B (8 hours) provide fan in-depth presentation of both 2D and 3D
Computer Vision and Image Analysis theory and their applications in
the above-mentioned diverse domains. Edge detection will allow to
extract reliable object contours.  Region segmentation and Texture
description will detail segmentation of an image into homogeneous
regions. Either edge or region object descriptions will be employed in
2D object shape analysis. 3D Computer Vision starts with a detailed
presentation of image acquisition and camera geometry, including
camera calibration. Then, two lectures on a) Stereo and Multiview
imaging and b) Structure from motion will provide the theoretical and
algorithmic tools to recover 3D world models from images. They will be
used on Localization and mapping that is of primary importance in
Autonomous Systems and Robotic perception. Finally, Object tracking is
presented, as it is of primary importance (together with object
detection presented in the ML DNN e-course) in practically all the
above-mentioned Computer Vision applications and way beyond.

Course lectures

Part A Image Processing (first day, 8 lectures):

    Introduction to Image Processing and Computer Vision
    Image Formation
    Image Sampling
    2D Systems
    Image Transforms
    Fast 2D Convolution Algorithms
    Image Perception
    Image Filtering


Part B Computer Vision  (second day, 8 lectures):

    Edge Detection
    Region Segmentation. Texture Description
    Shape Description
    Image Acquisition. Camera Geometry
    Stereo and Multiview Imaging
    Structure from Motion
    3D Robot Localization and Mapping
    Object Tracking

Though independent, the attendees of this short e-course will greatly
benefit by attending the CVML short e-course on "Machine Learning
and Deep Neural Networks" 17-18th February 2021:

CVML Short Course:  Machine Learning and Deep Neural Networks

You can use the following link for course registration:



Lecture topics, sample lecture ppts and videos, self-assessment questionnaires and programming exercises can be found therein.

For questions, please contact: Ioanna Koroni 


The short course is organized by Prof. I. Pitas, IEEE and EURASIP
fellow, Chair of the IEEE SPS Autonomous Systems Initiative, Director
of the Artificial Intelligence and Information analysis Lab (AIIA
Lab), Aristotle University of Thessaloniki, Greece, Coordinator of the
European Horizon2020 R&D project Multidrone. He is ranked 249-top
Computer Science and Electronics scientist internationally by
Guide2research (2018). He is head of the EC funded AI doctoral school
of Horizon2020 EU funded R&D project AI4Media (1 of the 4 in
Europe). He has 32200+ citations to his work and h-index 85+.


AUTH is ranked 153/182 internationally in Computer
Science/Engineering, respectively, in USNews ranking.


Relevant links:

1) Prof. I. Pitas:


2) Horizon2020 EU funded R&D project Aerial-Core: https://aerial-core.eu/

3) Horizon2020 EU funded R&D project Multidrone: https://multidrone.eu/

4) Horizon2020 EU funded R&D project AI4Media: https://ai4media.eu/

5) AIIA Lab: https://aiia.csd.auth.gr/



Sincerely yours

Prof. I. Pitas

Director of the Artificial Intelligence and Information analysis Lab (AIIA Lab)

Aristotle University of Thessaloniki, Greece