Blind steganalysis : a countermeasure for binary image steganography

In this paper, we propose a new blind steganalytic method to detect the presence of secret messages embedded in black and white images using the steganographic techniques. We start by extracting several sets of matrix, such as run length matrix, gap length matrix and pixel difference. We also apply characteristic function on these matrices to enhance their discriminative capabilities. Then we calculate the statistics which include mean, variance, kurtosis and skewness to form our feature sets. The presented empirical works demonstrate our proposed method can effectively detect three different types of steganography. This proves the universality of our proposed method as a blind steganalysis. In addition, the experimental results show our proposed method is capable of detecting small amount of the embedded message.

Estimating hidden message length in binary image embedded by using boundary pixels steganography

In this paper, we propose a new steganalytic method to detect the message hidden in a black and white image using the steganographic technique developed by Liang, Wang and Zhang. Our detection method estimates the length of hidden message embedded in a binary image. Although the hidden message embedded is visually imperceptible, it changes some image statistic (such as inter-pixels correlation). Based on this observation, we first derive the 512 patterns histogram from the boundary pixels as the distinguishing statistic, then we compute the histogram difference to determine the changes of the 512 patterns histogram induced by the embedding operation. Finally we propose histogram quotient to estimate the length of the embedded message. Experimental results confirm that the proposed method can effectively and reliably detect the length of the embedded message.

Design Pressure Test 2013 Workshop

Design Pressure Test 2013 was a full-day intensive design immersion creative event run on Saturday 3 August 2013, at the QUT Faculty of Creative Industries J Block Design Lab Workshop in Brisbane, Australia, for 25 self-selected high-achieving junior and middle school (year 5-9) students, as part of the Queensland Academies ‘Young Scholars’ Program. Facilitated by tertiary interior design, fashion design and industrial design educators, technicians and six tertiary interior design and fashion design students, the workshop explored design process, environmental impact, the material properties and structural integrity of cardboard, construction techniques, and the production and evaluation of furniture design prototypes. This action research study aimed to facilitate an awareness in young people, of the role and scope of design within our society, the environmental ramifications of design decisions, and the value of design thinking skills in generating strategies to solve basic to complex challenges. It also aimed to investigate the value of collaboration between junior and middle school students, tertiary design educators and students and industry professionals in design awareness, and inspiring post-secondary pathways and idea generation for education. During the creative event, students utilised mathematics skills and developed sketching, making, communication, presentation and collaboration skills to improve their design process, while considering social, cultural and environmental opportunities. Through a series of hands-on collaborative design experiments, participants explored in teams of five, the opportunities available using cardboard as a material – inspiring both functional and aesthetic design solutions. Underpinned by the State Library of Queensland Design Minds Website ‘inquire, ideate and implement’ model of design thinking, the experiments culminated in the development of a detailed client brief, the design and fabrication of a furniture item for seating, and then a team presentation of prototypes to a panel of judges from the professions of architecture, interior design and industrial design, viewed also by parents. The final test for structural integrity was measured by the hoisting down of an adult body weight onto the fabricated seat. The workshop was filmed for the television program ‘Totally Wild’ for dissemination nationally (over 200,000 viewing audience) of the value of design and the Design Minds model to a wider target youth audience.

Features-pooling blind jpeg image steganalysis

In this research, we introduce a new blind steganalysis in detecting grayscale JPEG images. Features-pooling method is employed to extract the steganalytic features and the classification is done by using neural network. Three different steganographic models are tested and classification results are compared to the five state-of-the-art blind steganalysis.

JPEG image steganalysis improvement via image-to-image variation minimization

In this research, we introduce an approach to enhance the discriminative capability of features by employing image-to-image variation minimization. In order to minimize image-to-image variation, we will estimate the cover image from the stego image by decompressing the stego image, transforming the decompressed image and recompressing back. Since the effect of the embedding operation in an image steganography is actually a noise adding process to the image, applying these three processes will smooth out the noise and hence the estimated cover image can be obtained.

New criterion for the stability of a human body in floodwaters

The authors must be congratulated for their original and important study. The flooding of urbanised areas constitutes a hazard to the population and infrastructure. Floods through inundated urban environments have been studied only recently and few considered the potential impact of flowing waters on pedestrians...

Residential balconies with road traffic noise : a combined source image and radiosity model

Several significant studies have been made in recent decades toward understanding road traffic noise and its effects on residential balconies. These previous studies have used a variety of techniques such as theoretical models, scale models and measurements on real balconies. The studies have considered either road traffic noise levels within the balcony space or inside an adjacent habitable room or both. Previous theoretical models have used, for example, simplified specular reflection calculations, boundary element methods (BEM), adaptations of CoRTN or the use of Sabine Theory. This paper presents an alternative theoretical model to predict the effects of road traffic noise spatially within the balcony space. The model includes a specular reflection component by calculating up to 10 orders of source images. To account for diffusion effects, a two compartment radiosity component is utilised. The first radiosity compartment is the urban street, represented as a street with building facades on either side. The second radiosity compartment is the balcony space. The model is designed to calculate the predicted road traffic noise levels within the balcony space and is capable of establishing the effect of changing street and balcony geometries. Screening attenuation algorithms are included to determine the effects of solid balcony parapets and balcony ceiling shields.

Dark Cartographies

‘Dark Cartographies’ is a slowly evolving meditation upon seasonal change, life after light and the occluding shadows of human influence. Through creating experiences of the many ‘times of a night’ the work allows participants to experience deep engagement with rich spectras of hidden place and sound. By amplifying and shining light upon a myriad of lives lived in blackness, ‘Dark Cartographies’ tempts us to re-understand seasonal change as actively-embodied temporality, inflected by our climate-changing disturbances. ‘Dark Cartographies’ uses custom interactive systems, illusionary techniques and real time spatial audio that draw upon a rich array of media, including seasonal, nocturnal field recordings sourced in the Far North Queensland region and detailed observations of foliage & flowering phases. By drawing inspiration from the subtle transitions between what Europeans named ‘Summer’ and ‘Autumn’, and by including the body and its temporal disturbances within the work, ‘Dark Cartographies’ creates compellingly immersive environments that wrap us in atmospheres beyond sight and hearing. ‘Dark Cartographies’ is a dynamic new installation directed & choreographed by environmental cycles; alluding to a new framework for making works that we call ‘Seasonal’. This powerful, responsive & experiential work draws attention to that which will disappear when biodiverse worlds have descended into an era of permanent darkness – an ‘extinction of human experience’. By tapping into the deeply interlocking seasonal cycles of environments that are themselves intimately linked with social, geographical & political concerns, participating audiences are therefore challenged to see the night, their locality & ecologies in new ways through extending their personal limits of perception, imagery & comprehension.

Guest editorial : the body and the law

This issue of the Journal of Law and Medicine seeks to explore the law's relationship with the human body within a broad context of social, cultural and technological considerations. It does this both in terms of the ways in which the law constitutes the body (for example, by labelling it as property or otherwise), and in terms of the legal rules which regulate rights to bodies and body parts.

Globalising the body : globalisation and reproductive rights

Globalisation is a phenomenon of the contemporary world. Everywhere around us there seem to be signs of the power of the forces of globalisation: in our media and popular culture; in our international linkages across continents through international travel and telecommunications; in our globalised trade; and with the global movement of people, a process which itself ranges from the movement of international tourists to the international movement of refugees and other displaced persons. The processes of globalisation seem to simultaneously unify and divide us. There is no doubt that we live in a globalised world and that we are connected to others in previously unimaginable ways by transportation, telecommunications and economics. Yet, while this global context increasingly links us to others, there is also a very real sense in which separation, difference and the local have also gained a new significance; we are locked in a tension between the universal and the particular that has come to typify contemporary society. This article explores the meanings of globalisation and this dynamic – or tension – between the universal and the particular in terms of its implications for the body and, in particular, its significance for women and their reproductive rights.

Systematic differences in membrane acyl composition associated with varying body mass in mammals occur in all phospholipid classes : an analysis of kidney and brain

The acyl composition of membrane phospholipids in kidney and brain of mammals of different body mass was examined. It was hypothesized that reduction in unsaturation index (number of double bonds per 100 acyl chains) of membrane phospholipids with increasing body mass in mammals would be made-up of similar changes in acyl composition across all phospholipid classes and that phospholipid class distribution would be regulated and similar in the same tissues of the different-sized mammals. The results of this study supported both hypotheses. Differences in membrane phospholipid acyl composition (i. e. decreased omega-3 fats, increased monounsaturated fats and decreased unsaturation index with increasing body size) were not restricted to any specific phospholipid molecule or to any specific phospholipid class but were observed in all phospholipid classes. With increase in body mass of mammals both monounsaturates and use of less unsaturated polyunsaturates increases at the expense of the long-chain highly unsaturated omega-3 and omega-6 polyunsaturates, producing decreases in membrane unsaturation. The distribution of membrane phospholipid classes was essentially the same in the different-sized mammals with phosphatidylcholine (PC) and phosphatidylethanolamine (PE) together constituting similar to 91% and similar to 88% of all phospholipids in kidney and brain, respectively. The lack of sphingomyelin in the mouse tissues and higher levels in larger mammals suggests an increased presence of membrane lipid rafts in larger mammals. The results of this study support the proposal that the physical properties of membranes are likely to be involved in changing metabolic rate.

Random projections on manifolds of symmetric positive definite matrices for image classification

Recent advances suggest that encoding images through Symmetric Positive Definite (SPD) matrices and then interpreting such matrices as points on Riemannian manifolds can lead to increased classification performance. Taking into account manifold geometry is typically done via (1) embedding the manifolds in tangent spaces, or (2) embedding into Reproducing Kernel Hilbert Spaces (RKHS). While embedding into tangent spaces allows the use of existing Euclidean-based learning algorithms, manifold shape is only approximated which can cause loss of discriminatory information. The RKHS approach retains more of the manifold structure, but may require non-trivial effort to kernelise Euclidean-based learning algorithms. In contrast to the above approaches, in this paper we offer a novel solution that allows SPD matrices to be used with unmodified Euclidean-based learning algorithms, with the true manifold shape well-preserved. Specifically, we propose to project SPD matrices using a set of random projection hyperplanes over RKHS into a random projection space, which leads to representing each matrix as a vector of projection coefficients. Experiments on face recognition, person re-identification and texture classification show that the proposed approach outperforms several recent methods, such as Tensor Sparse Coding, Histogram Plus Epitome, Riemannian Locality Preserving Projection and Relational Divergence Classification.

Matching image sets via adaptive multi convex hull

Traditional nearest points methods use all the samples in an image set to construct a single convex or affine hull model for classification. However, strong artificial features and noisy data may be generated from combinations of training samples when significant intra-class variations and/or noise occur in the image set. Existing multi-model approaches extract local models by clustering each image set individually only once, with fixed clusters used for matching with various image sets. This may not be optimal for discrimination, as undesirable environmental conditions (eg. illumination and pose variations) may result in the two closest clusters representing different characteristics of an object (eg. frontal face being compared to non-frontal face). To address the above problem, we propose a novel approach to enhance nearest points based methods by integrating affine/convex hull classification with an adapted multi-model approach. We first extract multiple local convex hulls from a query image set via maximum margin clustering to diminish the artificial variations and constrain the noise in local convex hulls. We then propose adaptive reference clustering (ARC) to constrain the clustering of each gallery image set by forcing the clusters to have resemblance to the clusters in the query image set. By applying ARC, noisy clusters in the query set can be discarded. Experiments on Honda, MoBo and ETH-80 datasets show that the proposed method outperforms single model approaches and other recent techniques, such as Sparse Approximated Nearest Points, Mutual Subspace Method and Manifold Discriminant Analysis.

Improved image set classification via joint sparse approximated nearest subspaces

Existing multi-model approaches for image set classification extract local models by clustering each image set individually only once, with fixed clusters used for matching with other image sets. However, this may result in the two closest clusters to represent different characteristics of an object, due to different undesirable environmental conditions (such as variations in illumination and pose). To address this problem, we propose to constrain the clustering of each query image set by forcing the clusters to have resemblance to the clusters in the gallery image sets. We first define a Frobenius norm distance between subspaces over Grassmann manifolds based on reconstruction error. We then extract local linear subspaces from a gallery image set via sparse representation. For each local linear subspace, we adaptively construct the corresponding closest subspace from the samples of a probe image set by joint sparse representation. We show that by minimising the sparse representation reconstruction error, we approach the nearest point on a Grassmann manifold. Experiments on Honda, ETH-80 and Cambridge-Gesture datasets show that the proposed method consistently outperforms several other recent techniques, such as Affine Hull based Image Set Distance (AHISD), Sparse Approximated Nearest Points (SANP) and Manifold Discriminant Analysis (MDA).

Joint 2D and 3D cues for image segmentation towards robotic applications

This thesis investigates the fusion of 3D visual information with 2D image cues to provide 3D semantic maps of large-scale environments in which a robot traverses for robotic applications. A major theme of this thesis was to exploit the availability of 3D information acquired from robot sensors to improve upon 2D object classification alone. The proposed methods have been evaluated on several indoor and outdoor datasets collected from mobile robotic platforms including a quadcopter and ground vehicle covering several kilometres of urban roads.