2. Professors
  3. NAPPI Michele
  4. Teaching

Foundations of Artificial Vision and Biometry

Michele NAPPI Foundations of Artificial Vision and Biometry

0522500084
DIPARTIMENTO DI INFORMATICA
EQF7
COMPUTER SCIENCE
2019/2020



YEAR OF COURSE 1
YEAR OF DIDACTIC SYSTEM 2016
SECONDO SEMESTRE
CFUHOURSACTIVITY
972LESSONS
MICHELE NAPPI T Curriculum
Objectives
KNOWLEDGE AND UNDERSTANDING

CRITICAL KNOWLEDGE OF THE FOUNDATIONS OF IMAGE BASED BIOMETRIC TECHNIQUES IN THE VARIOUS APPLICATION CONTEXTS.

APPLYING KNOWLEDGE AND UNDERSTANDING

THE STUDENT WHO WILL PROFITABLY FOLLOW THE COURSE:
•WILL KNOW THE MAIN ISSUES RELATED TO THE ANALYSIS AND SYNTHESIS OF BIOMETRIC SIGNALS;
• WILL BE ABLE TO UNDERSTAND THE LOGIC OF THE TRANSFORMS AND OPERATORS MOST WIDELY USED IN THE IMAGING CONTEXT;
• WILL BE ABLE TO CHOOSE THE TECHNIQUE BEST SUITED TO THE REFERENCE OPERATING ENVIRONMENT;
• WILL BE ABLE TO USE COMPARATIVE TOOLS TO MEASURE THE PERFORMANCE OF A GIVEN TECHNIQUE IN TERMS OF EFFICIENCY AND EFFECTIVENESS;
• WILL BE ABLE TO INDEPENDENTLY DESIGN AND IMPLEMENT IMPROVEMENT STRATEGIES BASED ON BASIC TECHNIQUES, IN PARTICULAR BY IDENTIFYING APPROPRIATE DESIGN SOLUTIONS FOR SPECIFIC MULTI-BIOMETRIC SYSTEMS;
• WILL BE ABLE TO SUPPORT CONVERSATIONS ON TOPICS RELATED TO THE CORE ASPECTS OF THE DISCIPLINE BY USING BOTH AN APPROPRIATE SCIENTIFIC TERMINOLOGY AND THE TOOLS OF MATHEMATICAL AND GRAPHIC REPRESENTATION OF THE MAIN DESCRIBED PHENOMENA;
• WILL PRODUCE MEDIUM-SIZED SOFTWARE PROJECTS IN C OR MATLAB
Prerequisites
STUDENT MUST HAVE BASIC KNOWLEDGE ABOUT BASIC ANALYSIS MATHS AND IMAGE PROCESSING.
Contents
1. ARTIFICIAL INTELLIGENCE AND COMPUTER VISION
2. IMAGE PROCESSING BASIC TECHNIQUES
3. VISUAL CONTEXT AWARE AND TRACKING
4. MACHINE LEARNING AND DEEP LEARNING IN COMPUTER VISION
5. VIDEO SECURITY SYSTEMS: A CASE STUDY
Teaching Methods
CLASS LECTURES INCLUDES LECTURES (6 ECTS) AND LABORATORY PROGRAMMING PRACTICE (3 ECTS). IN THE LABORATORY PRACTICE HOURS THE TEACHER WILL PROVIDE EXAMPLES OF PROGRAM WRITING (PHYTON\MATLAB\C LANGUAGE). DURING THE EXERCISES THE STUDENT WILL ADDRESS THE PROBLEM SOLVING IN THE COMPUTER VISION CONTEXT USING MACHINE LEARNING AND DEEP LEARNING. THE RESOLUTION METHOD CONSISTS IN UNDERSTANDING THE PROBLEM, IN DESIGNING A SOLUTION, AND FINALLY IN ITS IMPLEMENTATION. THE LAST PHASE INVOLVES ASSESSING THE VALIDITY OF THE SOLUTION AND VERIFYING THE CONSISTENCY AS WELL AS EFFECTIVENESS AND EFFICIENCY IN A COMPARATIVE CONTEXT.
Verification of learning
THE ACHIEVEMENT OF THE OBJECTIVES OF TEACHING IS CERTIFIED BY PASSING AN EXAMINATION WITH AN ASSESSMENT OUT OF THIRTY. THE EXAM INCLUDES A PRACTICAL TEST AND AN ORAL TEST. THE PRACTICAL TEST IS USED TO ASSESS THE CURRENT ABILITY OF THE STUDENT TO APPLY THE KNOWLEDGE ACQUIRED AND DEMONSTRATE COMPREHENSION SKILLS IN DEALING WITH A PRACTICAL PROBLEM IN PROGRAMMING, DESIGN AN ALGORITHMIC SOLUTION AND WRITE THE PROGRAM THAT SOLVES IT. THE PRACTICAL TEST IS PREPARATORY TO THE ORAL EXAMINATION, AND HAS A DURATION OF AT LEAST 60 MINUTES.

THE EXAM IS PASSED IF THE SCORE IS AT LEAST 18/30 , CORRESPONDING TO DEMONSTRATE TO HAVE CAPACITY TO IDENTIFY THE OPPORTUNITY ALGORITHMIC STRUCTURE OF THE RESOLUTION OF THE PROBLEM AND TO KNOW AT LEAST ADEQUATELY SETTING THE RELEVANT CODIFICATION IN LANGUAGE C. THE REACHING OF THE MAXIMUM SCORING, I.E. 30/30, IS OBTAINED WITH CORRECT AND COMPLETE DEVELOPMENT OF AN EFFECTIVE SOLUTION.

THE ORAL TEST CONSISTS IN AN INTERVIEW WITH QUESTIONS AND DISCUSSION ON THE THEORETICAL AND METHODOLOGICAL CONTENT INCLUDED IN THE SYLLABUS. IT IS AIMED TO VERIFY: 1. THE LEVEL OF KNOWLEDGE AND UNDERSTANDING ACHIEVED BY THE STUDENT; 2. THE EXPOSURE CAPABILITIES USING AN APPROPRIATE SCIENTIFIC TERMINOLOGY; 3. THE ABILITY OF AUTONOMOUS ORGANIZATION OF THE EXPOSURE ON THE SAME ARGUMENTS WITH THEORETICAL CONTENT. BOTH TESTS (WRITTEN OR PRACTICE AND ORAL) WILL IMPACT WITH EQUAL WEIGHT ON THE FINAL EVALUATION OF THE STUDENT.
DURING THE COURSE 2 TESTS IN ITINERE ARE SCHEDULED: A HALF COURSE TEST AND A FINAL ONE. BOTH ARE PERFORMED WITH THE SAME METHODS, OBJECTIVES AND EVALUATION OF THE WRITTEN OR PRACTICAL TEST. THE TEST IS PASSED IF THE WEIGHTED SUM OF THE 2 TEST SCORES IS GREATER THAN 18/30.
Texts
LEARNING MATERIAL (HANDOUTS, SLIDES, EXERCISES) IS AVAILABLE ON-LINE TO THE STUDENTS (EL-PLATFORM).
THE FOLLOWING BOOK IS NECESSARY FOR THE INDIVIDUAL STUDY.

1.MODERNE TECNICHE DI ELABORAZIONE DI IMMAGINI E BIOMETRIA, M. NAPPI E D. RICCIO, ATHENA EDITORE, 2008
2.DIGITAL IMAGE PROCESSING (THIRD EDITION), RAFAEL C. GONZALEZ AND PAUL WINTZ, ADDISON WESLEY, 1994
More Information
•TEACHING E-MAIL: MNAPPI@UNISA.IT
•TEACHING WEB SITE: BIPLAB.UNISA.IT,
WWW.UNISA.IT/DOCENTI/MICHELENAPPI/INDEX
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