Abstract: A method for discriminating and identifying, by 3D imaging, an object in a complex scene comprises the following steps: generating a sequence of 2D MIP images of the object, from a 3D voxel volume of the complex scene, this volume visualized by an operator by using an iterative process of MIP type from a projection plane and an intensity threshold determined by the operator on each iteration, automatically extracting, from the sequence of images, coordinates of a reduced volume corresponding to the sequence of images, choosing one of the intensity thresholds used during the iterations, automatically extracting, from the 3D volume of the complex scene, from the coordinates and chosen intensity threshold, a reduced 3D volume containing the object, automatically generating, from the reduced volume, by intensity threshold optimization, an optimized intensity threshold and an optimized voxel volume, a color being associated with each intensity, identifying the object by visualization.

Abstract: A method for 3D reconstruction of an object based on back-scattered and sensed signals, including: generating, from the sensed signals, 3D points to which their back-scattering intensity is respectively assigned, which form a set A of reconstructed data, starting from A, extracting a set B of data, whose points are located within a volume containing the object, as a function of volume characteristics F2, starting from B, extracting a set C of data characterizing the external surface of the object, the surface having regions with missing parts, depending on an extraction criterion, based on C, filling in the regions with missing parts by generation of a three-dimensional surface so as to obtain a set D of completed data of the object, without having to use an external database, and identifying the object based on D.

Abstract: A method for 3D reconstruction of an object based on back-scattered and sensed signals, including: generating, from the sensed signals, 3D points to which their back-scattering intensity is respectively assigned, which form a set A of reconstructed data, starting from A, extracting a set B of data, whose points are located within a volume containing the object, as a function of volume characteristics F2, starting from B, extracting a set C of data characterizing the external surface of the object, the surface having regions with missing parts, depending on an extraction criterion, based on C, filling in the regions with missing parts by generation of a three-dimensional surface so as to obtain a set D of completed data of the object, without having to use an external database, and identifying the object based on D.

Abstract: A method for synthetic reconstruction of objects includes: extracting criteria from a knowledge base; extracting, from sensed signals filtered by the criteria, weak signals; extracting, from the weak signals, weak signals of interest; removing noise from and amplifying the weak signals of interest and obtaining useful weak signals; identifying useful direct information, from useful weak signals filtered by the criteria and supplying optimum criteria; reconstructing, using the useful direct information, information of interest; reconstructing, using the information of interest, useful information and supplying optimum criteria; reconstructing, based on the useful information, three-dimensional information, supplying a recognition state file and supplying the optimum criteria; and updating the criteria with the optimum criteria.

Abstract: A method for synthetic reconstruction of objects includes: extracting criteria from a knowledge base; extracting, from sensed signals filtered by the criteria, weak signals; extracting, from the weak signals, weak signals of interest; removing noise from and amplifying the weak signals of interest and obtaining useful weak signals; identifying useful direct information, from useful weak signals filtered by the criteria and supplying optimum criteria; reconstructing, using the useful direct information, information of interest; reconstructing, using the information of interest, useful information and supplying optimum criteria; reconstructing, based on the useful information, three-dimensional information, supplying a recognition state file and supplying the optimum criteria; and updating the criteria with the optimum criteria.