To endow students with knowledge on characteristics and applications of sensors of diverse types and to deepen their knowledge about image processing.
José Manuel Matos Ribeiro da Fonseca
Weekly - 4
Total - Available soon
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
- 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
- It is considered a penalty of one value per day of delay in delivery of practical project.
- It is necessary to have at least 9,5 values on each evaluation component (pratical and theoretical).
Sensors technology: principles of functioning, acquisition of information, models, analysis of cases (sensors of presence and proximity, force and contact, temperature).
Ultrasounds Sensors: characteristics, processing of low-level sensorial information, feature extraction.
Image processing: from pixels to features, operations over images, segmentation, object detection, feature extraction, measures, analysis of applications.
Programs where the course is taught: