Imaging Security


Image & Video processing is part of many applications related to security: digital watermarking, steganography, image forensics, biometrics, and video surveillance.

  • Digital Watermarking allows owners or providers to hide an invisible and robust message inside a digital Multimedia document, mainly for security purposes such as owner or content authentication. There is a complex trade-off between the different parameters : capacity, visibility and robustness.
  • Steganographyis the art and science of writing hidden messages (in a picture or a video) in such a way that no-one apart from the sender and intended recipient even realizes there is a hidden message.
  • Image Forensics includes two main objectives: (1) To determine through which data acquisition device a given image is generated; (2) To determine whether a given image has undergone any form of modification or processing.
  • Biometrics: The security fields uses three different types of authentication : something you know, something you have, ore something you are : a biometric. Common physical biometrics includes fingerprints, hand geometry ; and retina, iris or facial characteristics. Behavioural characters include signature, voice. Ultimately, the technologies could find their strongest role as intertwined and complementary pieces of a multifactor authentication system. In the future biometrics is seen playing a key role in enhancing security, residing in smart cards and supporting personalized Web e-commerce services. Personalization through person authentication is also very appealing in the consumer product area. This course will focus on enabling technologies for Biometrics, with a particular emphasis on person verification and authentication based on or widely using image/video processing.
  • Video surveillance is the monitoring of the behavior, activities, or other changing information, usually of people for the purpose of influencing, managing, directing, or protecting. By default, for a better scene understanding, automatic image processing tools are used between acquisition/transmission and visualization or storage

Teaching and Learning Methods: Ce cours comporte un nombre limité de Travaux Pratiques et Travaux Dirigés.


Course Policies: Les TPs sont obligatoires.


Information hiding techniques for steganography and digital watermarking

Stefan Katzenbeisser, Fabien A. P. Petitcolas (Editors)

Hardcover, approx. 220 pages.
Artech House Books, December 1999
ISBN 1-58053-035-4

Akhtar, Zahid et al.

Biometrics: in search of identity and security: (Q & A)

IEEE Multimedia, Vol. PP, N°99, June 2017.

Redi, J. et al.

Digital image forensics : a booklet for beginners

Multimedia Tools and Applications, October 2010.

Turk, Matthew A and Pentland, Alex P. Face recognition using eigenfaces. Computer Vision and Pattern Recognition, 1991. Proceedings {CVPR'91.}, Computer Society Conference on 1991.


It would be good if you already have some knowledge about signal/image processing and coding, Matlab and OpenCv, but it is not mandatory.


The course is composed of a series of six 3-hour sessions:

-       Lecture on biometrics

-       Lab. session on Eigenfaces

-       Lecture on Digital watermarking, Steganography and Image Forensics

-       Lab. session on Image Integrity

-       Lecture on Video Surveillance

-       Problem Session on past exams.


Learning outcomes:  Become familiar with major image and video processing tools and techniques for security applications.

Nb hours: 21.00 (4 x 3 hours of lecture, 2 x 3 hours of laboratory, 1 x 3 hours of problems) 

Grading Policy:  Labs  (20%),  exam (80%)1-hour Multiple Choice Test Question (Closed-book examination).