Abstract:
Nowadays, urban and vehicular surveillance systems are collecting large amounts of image data for feeding recognition systems, for example, toward proposing localization or navigation services. In many cases, these image data cannot directly be processed in situ by the acquisition systems in reason of their low computational capabilities. The acquired images are transferred to remote computing servers through various computer networks, and then analyzed in details toward object recognition. The objective of this paper is twofold (i) presenting image-based ciphering methods that can efficiently be applied for securing the image transfer against consequences of image interceptions (e.g., man-in-the-middle attacks) (ii) presenting generic image-based analysis techniques that can be exploited for object recognition. Experimental results show end-to-end image-based solutions for fostering developments of surveillance systems and services in urban and vehicular environments.