A better understanding of MOX fuel in-pile behaviour requires a very detailed characterization of the Pu distribution in the pellet before and after irradiation. Electron probe microanalysis (EPMA) can be used to determine the distributions of chemical elements with a spatial resolution of 1 lm. This paper describes the development of X-ray microanalysis techniques to produce semi-quantitative 'maps' of plutonium concentrations in order to rapidly characterize large areas of the fuel microstructure (1 mm 2 ) with reasonable accuracy. A new segmentation technique based on statistical compatibility is then proposed, so as to finely describe the MIMAS MOX fuel microstructure. Two materials were finely characterized to demonstrate the reliability of this new method. In each case, the results demonstrate the good and reliable accuracy of this new characterization methodology. The analysis method used is currently able to identify three so-called phases (Pu-rich agglomerates, a coating phase and uranium-rich agglomerates), as well as to quantify the plutonium distribution and the plutonium content of these three phases. The impact of the fabrication process on the microstructure can be seen both in the surface distribution variations of the plutonium and in the local plutonium content variations.

In order to improve behavioral analysis systems in urban environments, this paper proposes, using data extracted from video surveillance cameras, a tracking method through two approaches. The first approach consists in comparing the position of people between two images of a video and to perform tracking by proximity. The second method using Kalman filters is based on the anticipation of the position of an individual in the upcoming image. The use of this method proves to be more efficient as it allows continuing a detection even when people cross each other or when they pass behind obstacles. The use of Kalman filters in this domain provides a new approach to obtain reliable tracking and information on speed and trajectory variations. The proposed method is innovative in the way the tracking is performed and the results are exploited. Experiments were conducted in a real situation and showed that the use of some elements of the first method could be reused to integrate a notion of distance in the method based on the Kalman filter and thus improve the latter both in tracking and in detecting of abnormal behavior. This article deals with the functioning of the two methods as well as the results obtained with the same scenarios. The experimentation concludes through concrete results that the Kalman filter method is more efficient than the proximity method alone. A sample result is available online for two of the seven videos used in this article (accessed on 19 July 2021).

Surveillance of a seaport can be achieved by different means: radar, sonar, cameras, radio communications and so on. Such a surveillance aims, on the one hand, to manage cargo and tanker traffic, and, on the other hand, to prevent terrorist attacks in sensitive areas. In this paper an application to video-surveillance of a seaport entrance is presented, and more particularly, the different steps enabling to classify mobile shapes. This classification is based on a parameter measuring the similarity degree between the shape under study and a set of reference shapes. The classification result describes the considered mobile in terms of shape and speed, as speed is determined by target tracking.

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