Signal & Image Processing and Analysis

Recommended Prerequisites

Calculus III ; Linear Algebra and Analytic Geometry; Applied Statistics ; Advanced Modelling and Simulation Techniques.

Teaching Methods

Since this is a discipline that aims to provide students with knowledge on effective handling, processing and analysis of signals and images, the teaching methodology emphasizes their involvement in “hand-on” tasks, wherever appropriate and possible. Thus, small groups will be formed to discuss the best ways of processing and analysis in various specific situations and report the results on a brief and effective way. The individual knowledge will be assessed through one or more individual tests.

Learning Outcomes

The purpose of this course is (i) to provide a general and integrated overview of the diversity of signals (taken in a broad sense) available in real world scenarios, such as laboratory and industrial applications, (ii) to demonstrate their utility and potential when properly processed, and (iii) to train the students in the proper use of techniques and methodologies for conducting such analysis. Furthermore, opportunities are provided for the application of the methodologies in practical situations, with real problems, in order to ensure a proper consolidation of the concepts discussed.

Work Placement(s)

No

Syllabus

I. Introduction. Basics on signal acquisition and processing. Applications of signal processing and analysis: chemical; inspection and quality control of products, supervision and control of processes; prediction of properties and states; process tomography; PAT).

II. Fundamentals on the use of transforms for signal and image processing. Signal processing 1D and 2D: signal improvement, filtering, smoothing and compression. Techniques to support the quantitative analysis of finely divided systems. Classification and pattern recognition methods. Image analysis and multivariate image analysis.

III. Applications. Process analytical technology (PAT). Industrial tomography: introduction and applications; detection techniques and selection of sensors; applications to multiphase systems. Applications with emphasis on inspection and quality control of products, supervision and control of processes.

Assessment Methods

Assessment
Mini Tests: 30.0%
Project: 70.0%

Bibliography

Openheim, AV; Schafer, RW. Discrete-Time Signal Processing. 2nd ed. Prentice-Hall. 1999.

Anil K. Jain, Fundamentals of Digital Image Processing. Prentice Hall Information and System Sciences Series, 2nd ed.

Marques, JS. Reconhecimento de padrões - métodos estatísticos e neuronais, IST Press, 2ª Edição.

R.A. Williams and M.S. Beck . Process Tomography: Principles Techniques and Applications. Butterworth Heinemann, 1995