Sensor Signal and Information Processing II

In the current age of information explosion, newly invented technological sensors and software are now tightly integrated with our everyday lives. Many sensor processing algorithms have incorporated some forms of computational intelligence as part of their core framework in problem solving. These algorithms have the capacity to generalize and discover knowledge for themselves and learn new information whenever unseen data are captured. The primary aim of sensor processing is to develop techniques to interpret, understand, and act on information contained in the data. The interest of this book is in developing intelligent signal processing in order to pave the way for smart sensors. This involves mathematical advancement of nonlinear signal processing theory and its applications that extend far beyond traditional techniques. It bridges the boundary between theory and application, developing novel theoretically inspired methodologies targeting both longstanding and emergent signal processing applications. The topic ranges from phishing detection to integration of terrestrial laser scanning, and from fault diagnosis to bio-inspiring filtering. The book will appeal to established practitioners, along with researchers and students in the emerging field of smart sensors processing

Passive Techniques for Detecting and Locating Manipulations in Digital Images

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Informática, leída el 19-11-2020El numero de camaras digitales integradas en dispositivos moviles as como su uso en la vida cotidiana esta en continuo crecimiento. Diariamente gran cantidad de imagenes digitales, generadas o no por este tipo de dispositivos, circulan en Internet o son utilizadas como evidencias o pruebas en procesos judiciales. Como consecuencia, el analisis forense de imagenes digitales cobra importancia en multitud de situaciones de la vida real. El analisis forense de imagenes digitales se divide en dos grandes ramas: autenticidad de imagenes digitales e identificacion de la fuente de adquisicion de una imagen. La primera trata de discernir si una imagen ha sufrido algun procesamiento posterior al de su creacion, es decir, que no haya sido manipulada. La segunda pretende identificar el dispositivo que genero la imagen digital. La verificacion de la autenticidad de imagenes digitales se puedellevar a cabo mediante tecnicas activas y tecnicas pasivas de analisis forense. Las tecnicas activas se fundamentan en que las imagenes digitales cuentan con \marcas" presentes desde su creacion, de forma que cualquier tipo de alteracion que se realice con posterioridad a su generacion, modificara las mismas, y, por tanto, permitiran detectar si ha existido un posible post-proceso o manipulacion...The number of digital cameras integrated into mobile devices as well as their use in everyday life is continuously growing. Every day a large number of digital images, whether generated by this type of device or not, circulate on the Internet or are used as evidence in legal proceedings. Consequently, the forensic analysis of digital images becomes important in many real-life situations. Forensic analysis of digital images is divided into two main branches: authenticity of digital images and identi cation of the source of acquisition of an image. The first attempts to discern whether an image has undergone any processing subsequent to its creation, i.e. that it has not been manipulated. The second aims to identify the device that generated the digital image. Verification of the authenticity of digital images can be carried out using both active and passive forensic analysis techniques. The active techniques are based on the fact that the digital images have "marks"present since their creation so that any type of alteration made after their generation will modify them, and therefore will allow detection if there has been any possible post-processing or manipulation. On the other hand, passive techniques perform the analysis of authenticity by extracting characteristics from the image...Fac. de InformáticaTRUEunpu

Digital forensic techniques for the reverse engineering of image acquisition chains

In recent years a number of new methods have been developed to detect image forgery. Most forensic techniques use footprints left on images to predict the history of the images. The images, however, sometimes could have gone through a series of processing and modification through their lifetime. It is therefore difficult to detect image tampering as the footprints could be distorted or removed over a complex chain of operations. In this research we propose digital forensic techniques that allow us to reverse engineer and determine history of images that have gone through chains of image acquisition and reproduction. This thesis presents two different approaches to address the problem. In the first part we propose a novel theoretical framework for the reverse engineering of signal acquisition chains. Based on a simplified chain model, we describe how signals have gone in the chains at different stages using the theory of sampling signals with finite rate of innovation. Under particular conditions, our technique allows to detect whether a given signal has been reacquired through the chain. It also makes possible to predict corresponding important parameters of the chain using acquisition-reconstruction artefacts left on the signal. The second part of the thesis presents our new algorithm for image recapture detection based on edge blurriness. Two overcomplete dictionaries are trained using the K-SVD approach to learn distinctive blurring patterns from sets of single captured and recaptured images. An SVM classifier is then built using dictionary approximation errors and the mean edge spread width from the training images. The algorithm, which requires no user intervention, was tested on a database that included more than 2500 high quality recaptured images. Our results show that our method achieves a performance rate that exceeds 99% for recaptured images and 94% for single captured images.Open Acces

Joint demosaicing and fusion of multiresolution coded acquisitions: A unified image formation and reconstruction method

Novel optical imaging devices allow for hybrid acquisition modalities such as compressed acquisitions with locally different spatial and spectral resolutions captured by a single focal plane array. In this work, we propose to model the capturing system of a multiresolution coded acquisition (MRCA) in a unified framework, which natively includes conventional systems such as those based on spectral/color filter arrays, compressed coded apertures, and multiresolution sensing. We also propose a model-based image reconstruction algorithm performing a joint demosaicing and fusion (JoDeFu) of any acquisition modeled in the MRCA framework. The JoDeFu reconstruction algorithm solves an inverse problem with a proximal splitting technique and is able to reconstruct an uncompressed image datacube at the highest available spatial and spectral resolution. An implementation of the code is available at https://github.com/danaroth83/jodefu.Comment: 15 pages, 7 figures; regular pape

Extracción y análisis de características para identificación, agrupamiento y modificación de la fuente de imágenes generadas por dispositivos móviles

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Informática, Departamento de Ingeniería del Software e Inteligencia Artificial, leída el 02/10/2017.Nowadays, digital images play an important role in our society. The presence of mobile devices with integrated cameras is growing at an unrelenting pace, resulting in the majority of digital images coming from this kind of device. Technological development not only facilitates the generation of these images, but also the malicious manipulation of them. Therefore, it is of interest to have tools that allow the device that has generated a certain digital image to be identified. The digital image source can be identified through the features that the generating device permeates it with during the creation process. In recent years most research on techniques for identifying the source has focused solely on traditional cameras. The forensic analysis techniques of digital images generated by mobile devices are therefore of particular importance since they have specific characteristics which allow for better results, and forensic techniques for digital images generated by another kind of device are often not valid. This thesis provides various contributions in two of the main research lines of forensic analysis, the field of identification techniques and the counter-forensics or attacks on these techniques. In the field of digital image source acquisition identification techniques, both closed and open scenarios are addressed. In closed scenarios, the images whose acquisition source are to be determined belong to a group of devices known a priori. Meanwhile, an open scenario is one in which the images under analysis belong to a set of devices that is not known a priori by the fo rensic analyst. In this case, the objective is not t he concrete image acquisition source identification, but their classification into groups whose images all belong to the same mobile device. The image clustering t echniques are of particular interest in real situations since in many cases the forensic analyst does not know a priori which devices have generated certain images. Firstly, techniques for identifying the device type (computer, scanner or digital camera of the mobile device) or class (make and model) of the image acquisition source in mobile devices are proposed, which are two relevant branches of forensic analysis of mobile device images. An approach based on different types of image features and Support Vector Machine as a classifier is presented. Secondly, a technique for the ident ification in open scenarios that consists of grouping digital images of mobile devices according to the acquisition source is developed, that is to say, a class-grouping of all input images is performed. The proposal is based on the combination of hierarchical grouping and flat grouping using the Sensor Pattern Noise. Lastly, in the area of att acks on forensic t echniques, topics related to the robustness of the image source identificat ion forensic techniques are addressed. For this, two new algorithms based on the sensor noise and the wavelet transform are designed, one for the destruction of t he image identity and another for its fo rgery. Results obtained by the two algorithms were compared with other tools designed for the same purpose. It is worth mentioning that the solution presented in this work requires less amount and complexity of input data than the tools to which it was compared. Finally, these identification t echniques have been included in a tool for the forensic analysis of digital images of mobile devices called Theia. Among the different branches of forensic analysis, Theia focuses mainly on the trustworthy identification of make and model of the mobile camera that generated a given image. All proposed algorithms have been implemented and integrated in Theia thus strengthening its functionality.Actualmente las imágenes digitales desempeñan un papel importante en nuestra sociedad. La presencia de dispositivos móviles con cámaras fotográficas integradas crece a un ritmo imparable, provocando que la mayoría de las imágenes digitales procedan de este tipo de dispositivos. El desarrollo tecnológico no sólo facilita la generación de estas imágenes, sino también la manipulación malintencionada de éstas. Es de interés, por tanto, contar con herramientas que permitan identificar al dispositivo que ha generado una cierta imagen digital. La fuente de una imagen digital se puede identificar a través de los rasgos que el dispositivo que la genera impregna en ella durante su proceso de creación. La mayoría de las investigaciones realizadas en los últimos años sobre técnicas de identificación de la fuente se han enfocado únicamente en las cámaras tradicionales. Las técnicas de análisis forense de imágenes generadas por dispositivos móviles cobran, pues, especial importancia, ya que éstos presentan características específicas que permiten obtener mejores resultados, no siendo válidas muchas veces además las técnicas forenses para imágenes digitales generadas por otros tipos de dispositivos. La presente Tesis aporta diversas contribuciones en dos de las principales líneas del análisis forense: el campo de las t écnicas de identificación de la fuente de adquisición de imágenes digitales y las contramedidas o at aques a est as técnicas. En el primer campo se abordan tanto los escenarios cerrados como los abiertos. En el escenario denominado cerrado las imágenes cuya fuente de adquisición hay que determinar pertenecen a un grupo de dispositivos conocidos a priori. Por su parte, un escenario abierto es aquel en el que las imágenes pertenecen a un conjunto de dispositivos que no es conocido a priori por el analista forense. En este caso el obj etivo no es la identificación concreta de la fuente de adquisición de las imágenes, sino su clasificación en grupos cuyas imágenes pertenecen todas al mismo dispositivo móvil. Las técnicas de agrupamiento de imágenes son de gran interés en situaciones reales, ya que en muchos casos el analist a forense desconoce a priori cuáles son los dispositivos que generaron las imágenes. En primer lugar se presenta una técnica para la identificación en escenarios cerrados del tipo de dispositivo (computador, escáner o cámara digital de dispositivo móvil) o la marca y modelo de la fuente en dispositivos móviles, que son dos problemáticas relevantes del análisis forense de imágenes digitales. La propuesta muestra un enfoque basado en distintos tipos de características de la imagen y en una clasificación mediante máquinas de soporte vectorial. En segundo lugar se diseña una técnica para la identificación en escenarios abiertos que consiste en el agrupamiento de imágenes digitales de dispositivos móviles según la fuente de adquisición, es decir, se realiza un agrupamiento en clases de todas las imágenes de ent rada. La propuesta combina agrupamiento jerárquico y agrupamiento plano con el uso del patrón de ruido del sensor. Por último, en el área de los ataques a las técnicas fo renses se tratan temas relacionados con la robustez de las técnicas forenses de identificación de la fuente de adquisición de imágenes. Se especifican dos algoritmos basados en el ruido del sensor y en la transformada wavelet ; el primero destruye la identidad de una imagen y el segundo falsifica la misma. Los resultados obtenidos por estos dos algoritmos se comparan con otras herramientas diseñadas para el mismo fin, observándose que la solución aquí presentada requiere de menor cantidad y complejidad de datos de entrada. Finalmente, estas técnicas de identificación han sido incluidas en una herramienta para el análisis forense de imágenes digitales de dispositivos móviles llamada Theia. Entre las diferentes ramas del análisis forense, Theia se centra principalmente en la identificación confiable de la marca y el modelo de la cámara móvil que generó una imagen dada. Todos los algoritmos desarrollados han sido implementados e integrados en Theia, reforzando así su funcionalidad.Depto. de Ingeniería de Software e Inteligencia Artificial (ISIA)Fac. de InformáticaTRUEunpu

The resolution enhancements of real-time captured images

Thesis (M.Eng. and S.B.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.Includes bibliographical references (leaves 77-78).This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.The resolution enhancement of real-time captured images is a problem that this thesis addresses in three ways. First, an improved color filter array interpolation algorithm is proposed, which offers high accuracy with reasonable performance. Second, the thesis discusses a mechanism in which real-time user feedback is given to aid in the capture and creation of mosaic images. Lastly, the practicality of these theoretical methods is evaluated by exploring their implementation. A system that was developed on a handheld computer platform for the purpose of proving the viability of these methods is investigated and assessed. The algorithms and methods proposed in this thesis achieve the objective of creating higher resolution images from real-time captured images.by Christopher J. Cheng.M.Eng.and S.B

The design and implementation of a stellar gyroscope for accurate angular rate estimation on CubeSats

Thesis (MEng)--Stellenbosch University, 2015.ENGLISH ABSTRACT: Until recently, small form factor satellites (such as CubeSats) relied almost exclusively on micro electromechanical system (MEMS) gyroscopes for attitude propagation purposes. Unfortunately, the nature of MEMS gyros is such that they exhibit a measure of bias drift. This drift must be compensated for, a task for which stellar gyros have proved to be exceptionally useful. Stellar gyros are satellite subsystems capable of inferring three-axis attitude propagation based on the displacement of a series of stars between successive image frames. Their design is analogous to that of star trackers, using many of the same hardware designs and algorithms. When used in combination with MEMS solutions, stellar gyros provide not only a means for drift compensation, but also a measure of functional redundancy with regard to attitude propagation. This thesis presents the design and implementation of stellar gyroscope algorithms capable of operating alongside existing orientation algorithms on traditional star tracker hardware. The CubeStar star tracker module is used as development platform. The proposed stellar gyro solution retains CubeStar’s existing star extraction algorithms, while investigating alternative methods for star centroiding in addition to the existing centre of gravity (CoG) approach. A dynamic proximity based matching algorithm is suggested to determine star correspondence between image frames. Finally, various well established estimation algorithms are considered for the purpose of rate determination, including singular value decomposition (SVD), Davenport’s q-Method and weighted least-squares (WLS). An initial evaluation of the proposed algorithms is made based on simulations in the MATLAB environment. Simulation results are confirmed through means of practical tests, performed on a simulated night sky in a controlled environment. With a focus on low angular rates, results suggest reliable operation up to ±1 deg/s in all three axes of rotation. As expected for stellar imaging solutions, angular rates estimated in both cross-boresight axes are almost an order of magnitude more accurate than the corresponding estimates in the boresight axis itself.AFRIKAANSE OPSOMMING: Mikrosatelliete, soos CubeSats, het tot onlangs byna uitsluitlik op mikro elektromeganiese (MEMS) vibrerende struktuur giroskope staatgemaak vir die meet van hoeksnelhede. Ongelukkig is die aard van MEMS giroskope sodanig dat hierdie metings afsette toon wat al hoe verder van hul werklike waardes verskuif. Daar moet gekompenseer word vir hierdie verskuiwing, ’n taak waarvoor stergiroskope besonder geskik is. Sterrebeeld gebaseerde giroskope (of bloot gewoon stergiroskope) is satelliet substelsels wat daartoe in staat is om ’n satelliet se oriëntasie in drie dimensies te propageer deur gebruik te maak van die verplasing van ’n reeks sterre tussen twee opeenvolgende beelde. Hulle ontwerp in terme van beide hardeware en algoritmes is soortgelyk aan dié van stervolger kameras. Stergiroskope kan ook saam met MEMS toestelle gebruik word. Hulle verskaf beide ’n metode om te kompenseer vir verskuiwings in MEMS metings sowel as ’n funksionele alternatief met betrekking tot hoekafskatting. Hierdie tesis beskryf die ontwerp en implementering van ster giroskoop algoritmes wat in staat is om hand-in-hand met bestaande oriëntasie algoritmes op tradisionele ster volger hardeware te funksioneer. Die CubeStar stervolger module is as ontwikkelings platform gebruik. Die beoogde stergiroskoop ontwerp behou CubeStar se bestaande ster ontginnings algoritmes. Verskeie metodes benewens die bestaande swaartepunt benadering word wel ondersoek vir die bepaling van ster sentroïedes. Die korrespondensie tussen opeenvolgende sterbeelde word bepaal deur middel van ’n dinamiese nabyheid gebaseerde passings algoritme. Ten slotte word verskeie algoritmes oorweeg vir die afskatting van ’n satelliet se hoeksnelhede. Dit sluit in enkelvoud waarde ontbinding (SVD), Davenport se q-metode en ’n geweegte kleinste kwadraat (WLS) benadering. Die voorgestelde algoritmes is ge-evalueer op grond van simulasies in die MATLAB omgewing. Praktiese toetse is uitgevoer op ’n gesimuleerde sterrebeeld om simulasie resultate te bevestig. Met ’n fokus op lae hoeksnelhede dui resultate op betroubare afskatting teen hoeksnelhede van tot ±1 grade/s rondom al drie rotasie-asse. Soos verwag van ster kameras is die hoekafskattings rondom die transversale asse ’n orde meer akkuraat as die ooreenstemmende afskattings rondom die optiese as