Luigi De Dominicis

Underwater three-dimensional imaging with an amplitude-modulated laser radar at a 405 nm wavelength

We report the results of underwater imaging with an amplitude-modulated single-mode laser beam and miniaturized piezoactuator-based scanning system. The basic elements of the device are a diode laser source at 405 nm with digital amplitude modulation and a microscanning system realized with a small-aperture aspheric lens mounted on a pair of piezoelectric translators driven by sawtooth waveforms. The system has been designed to be a low-weight and rugged imaging device suitable to operate at medium range (approximately 10 m) in clear seawater as also demonstrated by computer simulation of layout performance. In the controlled laboratory conditions a submillimeter range accuracy has been obtained at a laser amplitude modulation frequency of 36.7 MHz.

Using retinex for point selection in 3D shape registration

Inspired by retinex theory, we propose a novel method for selecting key points from a depth map of a 3D freeform shape; we also use these key points as a basis for shape registration. To find key points, first, depths are transformed using the Hotelling method and normalized to reduce their dependence on a particular viewpoint. Adaptive smoothing is then applied using weights which decrease with spatial gradient and local inhomogeneity; this preserves local features such as edges and corners while ensuring smoothed depths are not reduced. Key points are those with locally maximal depths, faithfully capturing shape. We show how such key points can be used in an efficient registration process, using two state-of-the-art iterative closest point variants. A comparative study with leading alternatives, using real range images, shows that our approach provides informative, expressive, and repeatable points leading to the most accurate registration results. HighlightsA novel method of key point detection from given 3D freeform shapes is proposed.The detected points are useful for efficient registration of 3D freeform shapes.Evaluation based on real range images shows that better results are obtained.

Regularization Based Iterative Point Match Weighting for Accurate Rigid Transformation Estimation

Feature extraction and matching (FEM) for 3D shapes finds numerous applications in computer graphics and vision for object modeling, retrieval, morphing, and recognition. However, unavoidable incorrect matches lead to inaccurate estimation of the transformation relating different datasets. Inspired by AdaBoost, this paper proposes a novel iterative re-weighting method to tackle the challenging problem of evaluating point matches established by typical FEM methods. Weights are used to indicate the degree of belief that each point match is correct. Our method has three key steps: (i) estimation of the underlying transformation using weighted least squares, (ii) penalty parameter estimation via minimization of the weighted variance of the matching errors, and (iii) weight re-estimation taking into account both matching errors and information learnt in previous iterations. A comparative study, based on real shapes captured by two laser scanners, shows that the proposed method outperforms four other state-of-the-art methods in terms of evaluating point matches between overlapping shapes established by two typical FEM methods, resulting in more accurate estimates of the underlying transformation. This improved transformation can be used to better initialize the iterative closest point algorithm and its variants, making 3D shape registration more likely to succeed.

IR multiple-photon excitation of polyatomic molecules: a route towards nanostructures

The availability of high power IR laser sources in the 1980s paved the way to new attractive experiments for driving chemical reactions, based on the selective excitation of vibrational modes in polyatomic molecules up to and above the dissociation threshold. The process was first studied in the collisionless regime for applications to laser isotope separation and selective chemistry, and later in collision-assisted conditions leading to the synthesis of nanostructures. In particular, the mechanisms of IR laser pyrolysis of SiH4 and hydrocarbons were investigated in order to control the production of silicon- and carbon-based nanoaggregates. For this purpose, different on-line diagnostics were utilized to monitor the gas-phase reaction intermediates and the process of particle nucleation and growth. The basic principles of the process of multiple-photon excitation of polyatomic molecules and its applications to the synthesis of nanostructures will be reviewed in this paper. Peculiar optical properties of silicon nanoparticles and carbon nanotubes obtained as final products of the developed processes will be described in relation to remarkable applications in several fields.

Detection of ethylene traces by photoacoustic spectroscopy

A laser based photoacoustic system has been designed and built at ENEA in order to monitor bio-gases produced in different processes involving living cells. Experiments aimed to reveal traces of ethylene emitted from tomato plantlets and fruits under temperature stress are here presented and discussed.

Accurately estimating rigid transformations in registration using a boosting-inspired mechanism

Feature extraction and matching provide the basis of many methods for object registration, modeling, retrieval, and recognition. However, this approach typically introduces false matches, due to lack of features, noise, occlusion, and cluttered backgrounds. In registration, these false matches lead to inaccurate estimation of the underlying transformation that brings the overlapping shapes into best possible alignment. In this paper, we propose a novel boosting-inspired method to tackle this challenging task. It includes three key steps: (i) underlying transformation estimation in the weighted least squares sense, (ii) boosting parameter estimation and regularization via Tsallis entropy, and (iii) weight re-estimation and regularization via Shannon entropy and update with a maximum fusion rule. The process is iterated. The final optimal underlying transformation is estimated as a weighted average of the transformations estimated from the latest iterations, with weights given by the boosting parameters. A comparative study based on real shape data shows that the proposed method outperforms four other state-of-the-art methods for evaluating the established point matches, enabling more accurate and stable estimation of the underlying transformation. HighlightsWe provide a novel method for evaluating point matches established by typical methods.Real data based experimental results show that the method outperforms the state-of-the-art.Under certain conditions, the finally estimated underlying transformation is optimal.The transformation can be recovered with an error as small as 5% from typical point matches.

Imaging topological radar technology as a general purpose instrument for remote colorimetric assessment, structural security, cataloguing, and dissemination

Abstract While today 3D digitisation techniques are commonly applied in several areas of cultural heritage, introducing new ways for monitoring, cataloguing, and studying masterpieces, the use of these technologies is not always worthwhile in terms of costs/benefits. The ENEA UTAPRAD-DIM laboratory has developed opto-electronic devices for cultural heritage applications. Two different 3D laser scanners for terrestrial and underwater inspection have been the subject of laboratory research for the last decade and a new technique known as imaging topological radar (ITR) has been developed and patented. The ITR system is based on the superimposition of three amplitude-modulated laser sources for the simultaneous acquisition of data related to colour and structure. This approach opens new scenarios for colour measurement and remote/non-invasive analysis, reducing the gap between costs and benefits from the technology. Several factors affect the quality of data collected by ITR, such as the precision of the scanner mechanism, the material and shape of the work studied, and the geometry of scanning (i.e. distance and angular dependencies). This paper explores the effect of the geometry of scanning on point cloud quality, focussing attention on data correction algorithms and their practical application. The data collected during the digitisation of the Sistine Chapel using the RGB-ITR scanner serve as a case study for validating the theoretical assumptions, models, and algorithms.

Illumination Normalization Using Weighted Gradient Integral Images

Captured images arise through interaction between objects of interest and illuminating light sources. If the latter are unevenly distributed, or are too strong or too weak, the image can have low contrast either locally or globally, impeding its interpretation and reducing its usefulness. In practice, control of illumination conditions is challenging, and not always possible. Thus, we propose a novel method to post-process captured images to reduce the effects of the illumination. We employ the Sobel operator to estimate gradients in the image, then use these gradients as weights in an averaging operation. To accelerate the operation, and remove certain unwanted features, integral images are iteratively calculated from the weighted images. This allows us to estimate the illumination component of the images, and in turn the reflectance component as their enhanced ones. A comparative study using a large number of images shows that the proposed algorithm outperforms several state of the art approaches.

NIR and UV spectroscopic techniques as tools to control nanoparticle growth in laser pyrolysis process

Due to the foreseen possibility of technological applications, there is an increasing interest in nanocrystalline soft materials, especially in iron silicon alloys. The synthesis of nanoparticles by means of CO2 laser induced pyrolisys is an important method for the production of the latter material with high purity upon well controlled conditions. In this production process, implying fast ultrafine powders condensation from the gas phase, the temperature is a key parameter, since the particles size is strongly affected by its variations. The potentialities of laser spectroscopic methods in the ultraviolet and infrared spectral region to monitor nanoparticles growth in a semi-industrial flow reactor for production of Si and FeSi nanoparticles and operating in ENEA, are explored in the present work.

Possibilities of NOx online control by using degenerate four wave mixing spectroscopy on intermediate species

The DFWM, used as a laser spectroscopy for gas phase trace detection, is receiving a great deal of attention for on- line applications in industrial combustion diagnostics. Low release of NOx requires a complete control of nascent NO formation, i.e. of the combustion chemistry involving the OH radical, and space resolved temperature measurements of each species. Both NO and OH have been detected on small hydrocarbon/air flames by DFWM in forward BOXCARS geometry. NO distribution has been investigated by exciting of (gamma) band, temperature and concentration have been calculated after spectral simulation and calibration on doped flames. HO spectra of the A2(Sigma) + - X2(Pi) , on the fundamental and first vibrationally excited transition, have been used to monitor the radical space distribution and its temperature. Line broadening, shifting and intensity borrowing phenomena related to saturation have been investigated in order to correctly model the spectra. The technique has been used to detect OH band in the combustion chamber of a dry low NOx 130 KW prototype burner, obtaining relative OH concentration profiles. A single shot broad band system, contemporary detection a few OH lines in the transition, has been built to operate in turbulent regime.