Hispars is an European EUCLID investigation project devoted to evaluation of Artificial Neural Networks for defense pattern applications. Three demonstrators representing three military operational contexts (Air-to-Ground, Ground Battlefield, Naval Threat Evaluation) have been defined and developed. A set of operational processing chains have been selected, and for each of them, ANN methods have been proposed and evaluated on real data at each level of processing, in comparison to those classical techniques used in existing equipement.
This paper deals with a Ph-D work about Automatic Target Recognition in Infrared aerial image sequences. The targets to be recognized are ground military vehicles like tanks or lorries...During the first step of the Automatic Target Recognition system simulation, the targets are segmented and tracked using an innovative active contour model. The active contour is based on snakes, robust statistics and it uses temporal information on the deformation of the target, such information being acquired during the sequence. This is performed in order to improve the tracking and the recognition to follow.The second step ofthe ATR system is the on-line recognition ofthe tracked and segmented objects. To that end, we use two modules based on pre-trained artificial neural networks. One is dedicated to target classification, the other to target identification. Both receive as input the Fourier descriptor of the extracted target shape.This method is validated both on Air-To-Ground JR seeker images and Ground JR camera images.
This paper adress objects tracking problem in an image sequence using an active contour model called "snake" based on energyminimizing curves with global constraints.Attempts to improve the robustness of these models is develop within the robust estimation theory leading a new cost function p in the new definition of energy : the resulting model is thus called p-snakes.Furthermore, we formulate a temporal continuity constraint in the energy definition: an incremental active contour model is suitable for objects tracking as it includes prediction.Experimental results on the p-snakes compared to classical snake are given on both synthetical and real IR images sequence.
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