To endow students with knowledge on characteristics and applications of sensors of diverse types and to deepen their knowledge about image processing.
- Knowledge of the C# programming language
- Implementation of image processing techniques with emphasis on the efficiency
- Real time programming
- Selection, project and implementation of sensor based circuits
- Sensors calibration
- Development of structured programming
- Usage of software libraries
- Project and implementation of sensors based circuits
José Manuel Matos Ribeiro da Fonseca
Weekly - 4
Total - 56
Basic knowledge in Electric Circuits Theory, Eletronics and Programming languages, namely, C or C# (C sharp) are recommended.
Interfacing sensors to the IBM PC, Willis J. Tompkins, John G. Webster, Prentice Hall
Multi-sensor fusion - fundamentals and applications with software, Richard Brooks, S. Iyengar. Prentice Hall
Digital Image Processing. Rafael Gonzalez, Paul Wintz. Addison-Wesley
Image Analysis: principles and practice, pp. 36 a 36 e 106 a 117. Joyce-Loebl
Digital Image Processing and Computer Vision, pp. 130 a 173. Robert Schalkoff
Fuzzy Algorithms, pp. 85 a 93, Zheru Chi, Hong Yan, Tuan Pham. Worls Scientific, Fuzzy Clustering
Computer Graphics - Principles and Practice, pp. 550 a 555. Foley, van DAM, Feiner, Hughes. Addison-Wesley
The Problem-solving sessions (TP) introduce the concepts and solve problems with the active participation of the students. In the laboratory sessions dedicated to image processing the students consolidate the concepts by developing a small image processing software project.
The fundamental concepts of the generic sensors component are presented on the TP sessions. On the laboratory sessions the students develop their knowledge of real world sensors by projecting and implementing small sensor based circuits that they calibrate and report the results.
In the last week of the course both practical assignments are presented and discussed with the teachers. The practical projects and their defense represent 40% of the final evaluation and the mid-term tests (or the final examination) the remaining 60%.
- 60 % Theoretical component
- 0,75 * GTT + 0,25 GTM
GTT = Average grade of 2 tests or Exam
GTM = Moodle Theoretical grade
- average grade of 9 moodle tests of a total of 10
- Moodle tests are to be done outsitde classes
Conditions: GTT >= 9.5 e GTM >= 9.5
- 40 % Pratical component
- 80% - 1st Project
- 20% - 2nd Project
Final Grade = TG * 0,6 + ( PPG1 *0,8 + PPG2 * 0,2 ) * 0,4
A penalty of 1 value per day of delay in the delivery of practical
work is considered
It is necessary to have a grade of not less than 9.5 in both practical
and theoretical components
Knowledge assessment tests and exams will be in person and without
consultation. Students who take remote assessment tests (tests or examss
(because they have an officially recognized status that allows them to
do so) may be called upon to defend the grade obtained in an oral
discussion with teachers that will be carried out in person or remote
according to the circumstances
The tests carried out remotely will be considered with consultation
for what they will have stated appropriate to the circumstances.
- Introduction – Typical steps of image processing
- Image formation: Pinhole, Lens, Aperture vs Depth of field and Aperture vs Shutter speed, Image sensors
- Basics of image processing: Geometric image transformations, Translation, Rotation and Scaling, Spatial methods, Linear and non-linear averaging, image averaging, median, k-nearest neighbor, Sigma, Roberts, Sobel and Quadtree, Binarization and binary image processing,Histogram, c-means and Otsu
- Image segmentation: Connected components and projections
- Feature extraction: Basic features calculation: chain code, Fresnell, Skeletoning (medial axis and Zhang and Suen)
- Sensors: Definitions, Sensors characterization, Sensors technology and applications. Examples of real world sensors – positioning, level, displacement, presence and movement, speed and acceleration, strength, flux, acoustic, humidity, powder, light and temperature.