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.

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.

Light of Extinction

Light of Extinction presents a diverse series of views into the complex antics of a semi-autonomous gaggle of robotic actants. Audiences initially enter into the 'backend' of the experience to be rudely confronted with the raw, messy operations of a horde of object-manipulating robotic forms. Seen through viewing apertures these ‘things’ deny any opportunity to grasp their imagined order. Audiences then flow on into the 'front end' of the work where now, seen through another aperture, the very same forms seemingly coordinate a stunning deep-field choreography, floating lusciously within inky landscapes of media, noise and embodied sound. As one series of conceptions slip into extinction, so others flow on in. The idea of the 'extinction of human experience' expresses a projected fear for that which will disappear when biodiverse worlds have descended into an era of permanent darkness. ‘Light Of Extinction' re-positions this anthropomorphic lament in order to suggest a more rounded acknowledgement of what might still remain - suggesting the previously unacknowledged power and place of autonomous, synthetic creation. Momentary disbelief gives way to a relieving celebration of the imagined birth of ‘things’ – without need for staples such as conventional light or the harmonious lullabies of long-extinguished sounds.

Tools for Mobile Multimedia Programming and Development

Mobile devices are rapidly developing into the primary technology for users to work, socialize, and play in a variety of settings and contexts. Their pervasiveness has provided researchers with the means to investigate innovative solutions to ever more complex user demands. Tools for Mobile Multimedia Programming and Development investigates the use of mobile platforms for research projects, focusing on the development, testing, and evaluation of prototypes rather than final products, which enables researchers to better understand the needs of users through image processing, object recognition, sensor integration, and user interactions. This book benefits researchers and professionals in multiple disciplines who utilize such techniques in the creation of prototypes for mobile devices and applications. This book is part of the Advances in Wireless Technologies and Telecommunication series collection.

The re-introduction project

The Re-introduction Project began with an art-science research residency in 2012, funded through the Australian 'Synapse' art-science residency program. It was developed in partnership with the Australian Wildlife Conservancy, Australia's largest private conservation agency and their South-East regional scientist Matt Hayward and conducted through a series of seven high intensity field-trips to AWC’s remote properties in VIC, NSW and SA. These trips coincided with key times at which the AWC’s mobile scientific teams were undertaking intensive scientific activities. The program coincided with specific events that senior scientist collaborator Dr Matt Hayward led in 2012 at Mallee Regions (Yookamurra, Scotia and Buckaringa), Lake Eyre Basin (Kalamurina) and Sydney (North Head). The initial outcome of the project was the work Pitfall (An Opportunistic Survey) - a new media installation created in light, media, object, text and sound presented near the AWC headquarters at Mildura in far NW Victoria. Pitfall built upon ideas and cross disciplinary processes developed during this residency/collaboration with Australian Wildlife Conservancy inspired by working with their ecological scientists during pitfall-trap survey events used to survey small mammals and invertebrates. ‘Pitfall’ was designed in response to a playful survey that I asked the AWC scientists to engage with around ideas of avoiding ecological pitfalls into the future. This continually-evolving artwork was built from multiple screens, a tabletop landscape mapped with projections, fibre optics, 3D spatial sound and infrared night imagery.

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).

Review: "Planning Asian cities : risks and resilience" edited by Stephen Hamnett and Dean Forbes, Planning, History and Environment Series, London, Routledge, 2011

Since the beginning of the agricultural revolution, cities have always been the cradle of civilisation, innovation and productivity, particularly as a result of the recent change factors affecting their (trans)formation, such as globalisation, the knowledge economy, technological advancements, climate change and so on. While in some parts of the world, cities are rapidly growing, in other parts, cities are shrinking, and their populations are aging. Even under the current pressure of constantly changing global conditions, the role of cities in influencing and partially shaping local, regional, national, supranational and even global level economy, society, environment and governance is undeniable. Global changes, while providing opportunities for cities and their administrations to reform and revisit existing planning and development processes and mechanisms, at the same time, challenge them by dealing with everincreasing risks and establishing resilience. At present, more than half of the world’s population...

Image-guided sampling reveals increased stroma and lower glandular complexity in mammographically dense breast tissue

Mammographic density (MD) adjusted for age and body mass index (BMI) is a strong heritable breast cancer risk factor; however, its biological basis remains elusive. Previous studies assessed MD-associated histology using random sampling approaches, despite evidence that high and low MD areas exist within a breast and are negatively correlated with respect to one another. We have used an image-guided approach to sample high and low MD tissues from within individual breasts to examine the relationship between histology and degree of MD. Image-guided sampling was performed using two different methodologies on mastectomy tissues (n = 12): (1) sampling of high and low MD regions within a slice guided by bright (high MD) and dark (low MD) areas in a slice X-ray film; (2) sampling of high and low MD regions within a whole breast using a stereotactically guided vacuum-assisted core biopsy technique. Pairwise analysis accounting for potential confounders (i.e. age, BMI, menopausal status, etc.) provides appropriate power for analysis despite the small sample size. High MD tissues had higher stromal (P = 0.002) and lower fat (P = 0.002) compositions, but no evidence of difference in glandular areas (P = 0.084) compared to low MD tissues from the same breast. High MD regions had higher relative gland counts (P = 0.023), and a preponderance of Type I lobules in high MD compared to low MD regions was observed in 58% of subjects (n = 7), but did not achieve significance. These findings clarify the histologic nature of high MD tissue and support hypotheses regarding the biophysical impact of dense connective tissue on mammary malignancy. They also provide important terms of reference for ongoing analyses of the underlying genetics of MD.

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.

Scleral matrix metalloproteinases, serine proteinase activity and hydrational capacity are increased in myopia induced by retinal image degradation

In the avian model of myopia, retinal image degradation quickly leads to ocular enlargement. We now give evidence that regionally specific changes in ocular size are correlated with both biomechanical indices of scleral remodeling, e.g. hydration capacity and with biochemical changes in proteinase activities. The latter include a 72 kDa matrix metalloproteinase (putatively MMP-2), other gelatin-binding MMPs, an acid pH MMP and a serine protease. Specifically, we have found that increases in scleral hydrational capacity parallel increases in collagen degrading activities. Gelatin zymography reveals that eyes with 7 days of retinal image degradation have elevated levels (1.4-fold) of gelatinolytic activities at 72 and 67 kDa M(r) in equatorial and posterior pole regions of the sclera while, after 14 days of treatment, increases are no longer apparent. Lower M(r) zymographic activities at 50, 46 and 37 kDa M(r) are collectively increased in eyes treated for both 7 and 14 days (1.4- and 2.4-fold respectively) in the equator and posterior pole areas of enlarging eyes. Western blot analyses of scleral extracts with an antibody to human MMP-2 reveals immunoreactive bands at 65, 30 and 25 kDa. Zymograms incubated under slightly acidic conditions reveal that, in enlarging eyes, MMP activities at 25 and 28 kDa M(r) are increased in scleral equator and posterior pole (1.6- and 4.5-fold respectively). A TIMP-like protein is also identified in sclera and cornea by Western blot analysis. Finally, retinal-image degradation also increases (~2.6-fold) the activity of a 23.5 kDa serine proteinase in limbus, equator and posterior pole sclera that is inhibited by aprotinin and soybean trypsin inhibitor. Taken together, these results indicate that eye growth induced by retinal-image degradation involves increases in the activities of multiple scleral proteinases that could modify the biomechanical properties of scleral structural components and contribute to tissue remodeling and growth.