CODE 80411 ACADEMIC YEAR 2016/2017 CREDITS 6 cfu anno 2 INFORMATICA 9014 (LM-18) - SCIENTIFIC DISCIPLINARY SECTOR INF/01 LANGUAGE Italiano (Inglese a richiesta) TEACHING LOCATION SEMESTER 1° Semester TEACHING MATERIALS AULAWEB AIMS AND CONTENT TEACHING METHODS Class (44 hours), lab (12 hours), project (50 hrs) and outside preparation Students are required to attend class and lab for a total of 6 hrs/week SYLLABUS/CONTENT Syllabus Students will learn basic tools for analysing 1-D and 2-D signals in the space and in the frequency domains. Particular attention will be devoted to filters, to deal with noise attenuation and feature enhancement. Dynamic filters will also be considered. The course will also cover low level vision topics, including image feature extraction, image segmentation,image registration, and image matching. Students will be involved in project activities. CONTENT: Systems - Systems: Input/Output signal, Response of a System - Systems Properties: Linearity, Time-invariance, Causality 1D signals - Complex numbers, Periodic Functions, Complex Functions, Trigonometric Polynomial - Fourier Series - Fourier Transform - Noise - Sampling, Sampling Theorem - Convolution Theorem - Filters - Kalman Filter - Wavelets 2D signals - Greyscale Images - Color images - Histogram - 2d Fourier Transform - Spatial filters - Image features (corner, edge, ridge) - Image matching - Image similarity measures RECOMMENDED READING/BIBLIOGRAPHY Signals and Systems Oppenheim et al. - Signals and Systems Bertoni et al. - Introduzione all’elaborazione dei segnali (UniMi) (in Italian) Digital Signal Processing Orfanidis - Introduction to Signal Processing Oppenheim et al. - Discrete-Time Signal Processing Signal & Image processing Gonzales Woods - Digital Image Processing Mallat - A wavelet tour of signal processing TEACHERS AND EXAM BOARD ANNALISA BARLA Ricevimento: Appointment by email PATRIZIA BOCCACCI Ricevimento: Send a mail to patrizia.boccacci@unige.it to make an appointment LESSONS Class schedule The timetable for this course is available here: Portale EasyAcademy EXAMS EXAM DESCRIPTION The final evaluation will take into account: (1) class attendance, (2) planned homework, (3) project discussion (4) oral dissertation ASSESSMENT METHODS The project should be written clearly, complemented with working code and it should show that the student has fully understood the topic. Examples on different real scenarios are encouraged. The oral examination consists in a discussion of the project and of the topics taught in class.
