Unmanned Aerial Systems (UAS) are extensively used in diverse fields, wherever inexpensive and easy-to-deploy platforms are required for close-range remote sensing.
Applications proposed in archaeology to date include ortho-photography and 3-D modeling. On the other hand, use of image processing and feature detection methods, well developed in other fields is hardly used.
After reviewing technologies and methods for UAS-based surveying and surface modeling, we propose feature detection methods (e.g. line detection, texture segmentation) dedicated to extraction of structures in the images that are significant for archaeological survey, planning, and documentation and show results on selected case studies.
This work, after a preliminary feasibility study using a Matlab environment simulation, defines the design and the real
hardware testing of a new bio-inspired decision chain for UAV sense-and-avoid applications. Relying on a single and
cheap visible camera sensor, computer vision, bio-inspired and automatic decision algorithms have been adopted and
implemented on a specific ARM embedded platform through C++/OpenCV coding. A first data set processing, really
captured on flight, has been presented.
In this paper, starting from the GOFR algorithm, a new Forward Regression algorithm for landmine detection and
localization using thermal methods is presented. The efficiency of such algorithm is described by showing a valid
representation of the typical temperature waveforms taken after heating the ground surface, and detection of
temperature anomalies due to the presence of hidden objects. Optimizations to the algorithm are then showed, with the
aim of a significant sampling density reduction in space and time.
This paper presents new techniques of landmine detection and localization using thermal methods. Described methods
use both dynamical and static analysis. The work is based on datasets obtained from the Humanitarian Demining
Laboratory of Università La Sapienza di Roma, Italy.
In this paper we present results of experimental validation of a new methodology for anti-personnel mine (APM)
detection for humanitarian demining, proposed by the authors and previously validated only by simulation. The
technique is based on local heating and sensing by contactless thermometers (pyrometers). A large sand box (2.6m3) has
been realized and fitted with a cart moving on rails and holding instrumentation. Accurate mine surrogates have been
hidden in the sand together with confounders. Preliminary measurements are consistent with simulations and prove
validity of the approach.
In the framework of ARCHEO, a national research project funded by the Italian Ministry for Universities and Scientific and Technological Research (M.U.R.S.T.), a new ground penetrating radar (GPR) has been developed by the Italian Consortium for Research on Advanced Remote Sensing Systems (CO.RI.S.T.A.). The system has been specially designed to meet archaeological requirements and it will be tested the two archaeological sites of Sinuessa and Cales, in the Southern Italy. An innovative feature of ARCHEO concerns the exploitation of that of a multiview multistatic measurement scheme (at several frequencies) rather than a more common multimonostatic (or multibistatic). In order to reconstruct buried objects starting from the measurement data collected with such an acquisition strategy, it is made use of an inverse scattering technique. With the real project ARCHEO in mind (in particular this scheme of measurement), this paper deals with a theoretical discussion on the features of the class of retrievable profiles by G.P.R. data, within the framework of a linear model for electromagnetic scattering in a two dimensional lossless half space. For a given range of frequencies exploitable, multiview multistatic measurements can be useful in G.P.R. prospecting because they can provide information on low spatial harmonic components of an unknown object not attainable from the multimonostatic scheme exploiting the same frequency range. In particular, we show that, for a given band of work frequencies, the class of the unknowns retrievable by a multiview multistatic multifrequency measurement configuration can be is not much different from that attainable within a multimonostatic configuration with the addition of multiview multistatic data taken at the lowest of the frequencies adopted.
In the framework of ARCHEO, a national research project funded by the Italian Ministry for Universities and Scientific and Technological Research, a new ground penetrating radar has been developed by the Italian Consortium for Research on Advanced Remote Sensing Systems. The system has been specially designed to meet archaeological requirements and it will be used to identify and characterize buried finds. The paper summarizes the main guidelines followed during the design phase and presents the radar architecture.