In this paper, we give the design and implementation of a system for person re-identification in a camera network, based on the appearance. This system seeks to construct an online database that contains the history of every person that enters the field of view of the cameras. This system is qualified to associate an identifier to each detected person, which keeps this identifier in the same camera and in other cameras even if he or she disappears and then appears again. Our system comprises a moving objects detection step that is implemented using the Mixture of Gaussians method and a proposed difference method, to improve the detection results. It also comprises a tracking step that is implemented using the sum of squared differences algorithm. The re-identification stage is realized using two steps: the intersection of tracking and detection for the temporal association, the histogram for comparison. The global system was tested on a real data set collected by three cameras. The experimental results show that our approach gives very satisfactory results.