Sensorial Systems


To endow students with knowledge on characteristics and applications of sensors of diverse types and to deepen their knowledge about image processing.

General characterization





Responsible teacher

José Manuel Matos Ribeiro da Fonseca


Weekly - 4

Total - Available soon

Teaching language



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

Teaching method

Available soon

Evaluation method

Evaluation method:

  • 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).


Subject matter

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.