Mem Tri: Memory Forensics Triage Tool

This work explores the development of MemTri. A memory forensics triage tool that can assess the likelihood of criminal activity in a memory image, based on evidence data artefacts generated by several applications. Fictitious illegal suspect activity scenarios were performed on virtual machines to generate 60 test memory images for input into MemTri. Four categories of applications (i.e. Internet Browsers, Instant Messengers, FTP Client and Document Processors) are examined for data artefacts located through the use of regular expressions. These identified data artefacts are then analysed using a Bayesian Network, to assess the likelihood that a seized memory image contained evidence of illegal activity. Currently, MemTri is under development and this paper introduces only the basic concept as well as the components that the application is built on. A complete description of MemTri coupled with extensive experimental results is expected to be published in the first semester of 2017.

Reduced-Reference Image Quality Assessment Based on Edge Preservation

Assessing the subjective quality of processed images through an objective quality metric is a key issue in multimedia processing and transmission. In some scenarios, it is also important to evaluate the quality of the received images with minimal reference to the transmitted ones. For instance, for closed-loop optimisation of image and video transmission, the quality measure can be evaluated at the receiver and provided as feedback information to the system controller. The original images - prior to compression and transmission - are not usually available at the receiver side, and it is important to rely at the receiver side on an objective quality metric that does not need reference or needs minimal reference to the original images. The observation that the human eye is very sensitive to edge and contour information of an image underpins the proposal of our reduced reference (RR) quality metric, which compares edge information between the distorted and the original image. Results highlight that the metric correlates well with subjective observations, also in comparison with commonly used full-reference metrics and with a state-of-the-art reduced reference metric. © 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.

Adaptive self-calibrating image rejection receiver

An adaptive self-calibrating image rejection receiver is described, containing a modified Weaver image rejection mixer and a Digital Image Rejection Processor (DIRP). The blind source-separation-based DIRP eliminates the I/Q errors improving the Image Rejection Ratio (IRR) without the need for trimming or use of power-hungry discrete components. Hardware complexity is minimal, requiring only two complex coefficients; hence it can be easily integrated into the signal processing path of any receiver. Simulation results show that the proposed approach achieves 75-97 dB of IRR.

Design and low-power implementation of an adaptive image rejection receiver

This paper deals with and details the design and implementation of a low-power; hardware-efficient adaptive self-calibrating image rejection receiver based on blind-source-separation that alleviates the RF analog front-end impairments. Hybrid strength-reduced and re-scheduled data-flow, low-power implementation of the adaptive self-calibration algorithm is developed and its efficiency is demonstrated through simulation case studies. A behavioral and structural model is developed in Matlab as well as a low-level architectural design in VHDL providing valuable test benches for the performance measures undertaken on the detailed algorithms and structures.

Design of a power-aware digital image rejection receiver

This paper deals with and details the design of a power-aware adaptive digital image rejection receiver based on blind-source-separation that alleviates the RF analog front-end impairments. Power-aware system design at the RTL level without having to redesign arithmetic circuits is used to reduce the power consumption in nomadic devices. Power-aware multipliers with configurable precision are used to trade-off the image-rejection-ratio (IRR) performance with power consumption. Results of the simulation case studies demonstrate that the IRR performance of the power-aware system is comparable to that of the normal implementation albeit degraded slightly, but well within the acceptable limits.

Image, video and 3D data registration: medical, satellite and video processing applications with quality metrics

Data registration refers to a series of techniques for matching or bringing similar objects or datasets together into alignment. These techniques enjoy widespread use in a diverse variety of applications, such as video coding, tracking, object and face detection and recognition, surveillance and satellite imaging, medical image analysis and structure from motion. Registration methods are as numerous as their manifold uses, from pixel level and block or feature based methods to Fourier domain methods. This book is focused on providing algorithms and image and video techniques for registration and quality performance metrics. The authors provide various assessment metrics for measuring registration quality alongside analyses of registration techniques, introducing and explaining both familiar and state–of–the–art registration methodologies used in a variety of targeted applications.

Example-Based Face Shape Recovery Using the Zenith Angle of the Surface Normal

We present a method for recovering facial shape using an image of a face and a reference model. The zenith angle of the surface normal is recovered directly from the intensities of the image. The azimuth angle of the reference model is then combined with the calculated zenith angle in order to get a new field of surface normals. After integration of the needle map, the recovered surface has the effect of mapped facial features over the reference model. Experiments demonstrate that for the lambertian case, surface recovery is achieved with high accuracy. For non-Lambertian cases, experiments suggest potential for face recognition applications.