Francesca Uccheddu

Wavelet-based blind watermarking of 3D models

Watermarking of 3D meshes has received a limited attention due to the difficulties encountered in extending the algorithms developed for 1D (audio) and 2D (images and video) signals to topological complex objects such as meshes. Other difficulties arise from the wide variety of attacks and manipulations 3D watermarks should be robust to. For this reason, most of the 3D watermarking algorithms proposed so far adopt a non-blind detection. In this paper we present a new blind watermarking algorithm for 3D meshes. In order to simultaneously achieve watermark imperceptibility and robustness a multiresolution framework is adopted. To do so we assume that host meshes are semi-regular ones, a property that permits to first perform a wavelet decomposition and then to embed the watermark at a suitable resolution level. Watermark detection is accomplished by computing the correlation between the watermark signal and the to-be-inspected mesh. Robustness against geometric transformations such as rotation, translation and uniform scaling is achieved by embedding the watermark in a normalized version of the host mesh, obtained by means of Principal Component Analysis. Experimental results show the validity of the proposed algorithm both in terms of imperceptibility and robustness against a wide class of attacks including noise addition, smoothing and cropping.

Exploring Image Dependencies: a New Challenge in Image Forensics

Though the current state of the art of image forensics permits to acquire very interesting information about image history, all the instruments developed so far focus on the analysis of single images. It is the aim of this paper to propose a new approach that moves the forensics analysis further, by considering groups of images instead of single images. The idea is to discover dependencies among a group of images representing similar or equal contents in order to construct a graph describing image relationships. Given the pronounced effect that images posted on the Web have on opinions and bias in the networked age we live in, such an analysis could be extremely useful for understanding the role of pictures in the opinion forming process. We propose a theoretical framework for the analysis of image dependencies and describe a simple system putting the theoretical principles in practice. The performance of the proposed system are evaluated on a few practical examples involving both images created and processed in a controlled way, and images downloaded from the web.

Multimedia Forensic Techniques for Acquisition Device Identification and Digital Image Authentication

Multimedia forensics can be defined as the science that tries, by only analysing a particular digital asset, to give an assessment on such a content and to extract information that can be useful to address and support an investigation linked to the scene represented in that specific digital document. The basic idea behind multimedia forensics relies on the observation that both the acquisition process and any post-processing operation leave a distinctive imprint on the data, as a sort of digital fingerprint. The analysis of such a fingerprint may permit to determine image/video origin and to establish digital content authenticity. DOI: 10.4018/978-1-60566-836-9.ch006

A RGB-D based instant body-scanning solution for compact box installation

Body scanning presents unique value in delivering the first digital asset of a human body thus resulting a fundamental device for a range of applications dealing with health, fashion and fitness. Despite several body scanners are in the market, recently depth cameras such as Microsoft Kinect® have attracted the 3D community; compared with conventional 3D scanning systems, these sensors are able to capture depth and RGB data at video rate and even if quality and depth resolution are not optimal for this kind of applications, the major benefit comes from the overall acquisition speed and from the IR pattern that allows poor lighting conditions optimal acquisition. When dealing with non-rigid bodies, unfortunately, the use of a single depth camera may lead to inconsistent results mainly caused by wrong surfaces registration. With the aim of improving existing systems based on low-resolution depth cameras, the present paper describes a novel scanning system for capturing 3D full human body models by using multiple Kinect® devices in a compact setup. The system consists of an instantaneous scanning system using eight depth cameras, appropriately arranged in a compact wireframe. To validate the effectiveness of the proposed architecture, a comparison of the obtained 3D body model with the one obtained using a professional Konica Minolta Range Seven 3D scanner is also presented and possible drawbacks are hinted at.

On the Performance of the Intel SR30 Depth Camera: Metrological and Critical Characterization

Specifically conceived for applications related to face analytics and tracking, scene segmentation, hand/finger tracking, gaming, augmented reality, and RGB-D cameras are nowadays used even as 3-D scanners. Despite depth cameras’ accuracy and precision are not comparable with professional 3-D scanners, they still constitute a promising device for reverse engineering (RE) applications in the close range, due to their low cost. This is particularly true for more recent devices, such as, for instance, the RealSense SR300, which promises to be among the best performing close range depth cameras in the market. Given the potentiality of this new device, and since to date a deep investigation on its performances has not been assessed in scientific literature, the main aim of this paper is to characterize and to provide metrological considerations on the Intel RealSense SR300 depth sensor when this is used as a 3-D scanner. To this end, the device sensor performances are first assessed by applying the existing normative guidelines (i.e. the one published by the Association of German Engineers - Verein Deutscher Ingenieure - VDI/VDE 2634) both to a set of raw captured depth data and to a set acquired with optimized setting of the camera. Then, further assessment of the device performances is carried out by applying some strategies proposed in the literature using optimized sensor setting, to reproduce “real life” conditions for the use as a 3-D scanner. Finally, the performance of the device is critically compared against the performance of latest short-range sensors, thus providing a useful guide, for researchers and practitioners, in an informed choice of the optimal device for their own RE application.

Towards a CAD-based automatic procedure for patient specific cutting guides to assist sternal osteotomies in pectus arcuatum surgical correction

Abstract Pectus Arcuatum, a rare congenital chest wall deformity, is characterized by the protrusion and early ossification of sternal angle thus configuring as a mixed form of excavatum and carinatum features. Surgical correction of pectus arcuatum always includes one or more horizontal sternal osteotomies, consisting in performing a V-shaped horizontal cutting of the sternum (resection prism) by means of an oscillating power saw. The angle between the saw and the sternal body in the V-shaped cut is determined according to the peculiarity of the specific sternal arch. The choice of the right angle, decided by the surgeon on the basis of her/his experience, is crucial for a successful intervention. The availability of a patient-specific surgical guide conveying the correct cutting angles can considerably improve the chances of success and, at the same time, reduce the intervention time. The present paper aims to propose a new CAD-based approach to design and produce custom-made surgical guides, manufactured by using additive manufacturing techniques, to assist the sternal osteotomy. Starting from CT images, the procedure allows to determine correct resection prism and to shape the surgical guide accordingly taking into account additive manufacturing capabilities. Virtually tested against three case studies the procedure demonstrated its effectiveness.

A semi-automatic computer-aided method for personalized Vacuum Bell design

ABSTRACTPectus Excavatum, one of the most frequent chest wall deformities, is characterized by a depression of the sternum and costal cartilages. Patients with mild deformities are generally treated conservatively by using the so called Vacuum Bell (VB) i.e. a suction cup to be placed on the patients sternal region. Three different sizes, as well as a model fitted for young women, of VB are available on the market. Unfortunately, the variability of the surface to be treated, the possible asymmetry of the caved-in area and the prolonged use, can make the device uncomfortable and, in some cases, ineffective for the patient. In order to cope with these issues, the present paper proposes a computer-aided method for customized vacuum bell design to be used by non-expert user, e.g. by medical staff. In particular, the present work entails the development of a system comprising: 1) a dedicated software capable of acquiring the 3D chest geometry - by using a low-cost range sensor, i.e. Kinect v2 - and of process...

Identification of pictorial materials by means of optimized multispectral reflectance image processing

Image spectroscopy may allow identifying the materials present on a painting surface in a non-invasive way. The proposed method aims at optimizing, and thus reducing, the number of filters employed, while still providing a robust method, that achieves similar performances as traditional ones, which in turn employ a large number of filters. Moreover, we targeted the identification of the pigments present on the outer layer of a painting independently from their thickness, the underlying background or support, the binder employed, their aging and acquisition set-up. In order to achieve this objective, a relevant number of swatches have been prepared, on different supports and with different thicknesses and binding mediums. Spectral reflectance curves of such chemically known pictorial layers have been recorded by means of a spectrometer and a spectrophotometer. A novel Principal Component Analysis (PCA) based approach has been devised to select the most relevant wavebands, i.e. those that allow the most effective discrimination among (quasi)metameric colours, which are thus not to be distinguished with the naked eye or with an RGB camera. Comparisons of results using the 13 filters available on the filter wheel and of a selection of only 3 and 4 filters, support the idea of the simplified version investigated in this paper being a viable alternative.

Improving on fast and automatic texture mapping of 3D dense models

Not all range devices acquire, along with 3D data, the objects texture. Moreover, not always the desired texture is the visible light image. In such cases, currently, an “a posteriori” texturing of a 3D model is mostly performed in a manual or semi-automated fashion, resulting in a subjective and time consuming operation. Matching homologues points between 2D and 3D data in fact proved to be a more complex operation than image to image, or geometry to geometry registration. The method described in this paper is designed to be fully automated. The software takes as input a generic un-textured 3D model and a nonspecific texture image, which could be different from a visible light photograph, but belong to a set of diagnostic images like X rays, UV light, or IR images. It relies on the creation from the 3D model of several 2D depth maps which retains an exact correspondence with the points of the relief. Each depth map is generated from a different external “view point”. The number and location of such viewpoints is determined “a priori”, but their final position is to be changed and adjusted on a iterative and automatic base, to assure the possibility of an optimal choice. The selection of the best matching depth map is done by picking the depth map which shows the highest similarity with the texture image, based on a 2D-2D registration procedure performed on all generated depth maps. In order to speed up the procedure, a multi-resolution approach is adopted, where the coarse selection is performed on down-sampled images. Cross correlation and Maximization of Mutual Information (MMI) are here both used as similarity measures, exploiting their different and complementary performances depending on the image size.

Anticollusion watermarking of 3D meshes by prewarping

A novel pre-warping technique for 3D meshes is presented to prevent collusion attacks on fingerprinted 3D models. By extending a similar technique originally proposed for still images, the surface of watermarked 3D meshes is randomly and imperceptibly pre-distorted to protect embedded fingerprints against collusion attacks. The peculiar problems set by the 3D nature of the data are investigated and solved by preserving the perceptual quality of warped meshes. The proposed approach is independent of the chosen fingerprinting system. The proposed algorithm can be implemented inside a watermarking chain, as an independent block, before performing features extraction and watermark embedding. It follows that the detection algorithm is not influenced by the anti-collusion block. The application of different collusion strategies has revealed the dificulty for colluders to inhibit watermark detection while ensuring an acceptable quality of the attacked model.