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Multi evidence fusion scheme for content-based image retrieval by clustering localised colour and texture features
No full textContent-Based Image Retrieval (CBIR) is an automatic process of retrieving images according to their visual content. Research in this field mainly follows two directions. The first is concerned with the effectiveness in describing the visual content of images (i.e. features) by a technique that lead to discern similar and dissimilar images, and ultimately the retrieval of the most relevant images to the query image. The second direction focuses on retrieval efficiency by deploying efficient structures in organising images by their features in the database to narrow down the search space. The emphasis of this research is mainly on the effectiveness rather than the efficiency.
There are two types of visual content features. The global feature represents the entire image by a single vector, and hence retrieval by using the global feature is more efficient but often less accurate. On the other hand, the local feature represents the image by a set of vectors, capturing localised visual variations in different parts of an image, promising better results particularly for images with complicated scenes. The first main purpose of this thesis is to study different types of local features. We explore a range of different types of local features from both frequency and spatial domains. Because of the large number of local features generated from an image, clustering methods are used for quantizing and summarising the feature vectors into segments from which a representation of the visual content of the entire image is derived. Since each clustering method has a different way of working and requires settings of different input parameters (e.g. number of clusters), preparations of input data (i.e. normalized or not) and choice of similarity measures, varied performance outcomes by different clustering methods in segmenting the local features are anticipated. We therefore also intend to study and analyse one commonly used clustering algorithm from each of the four main categories of clustering methods, i.e. K-means (partition-based), EM/GMM (model-based), Normalized Laplacian Spectral (graph-based), and Mean Shift (density-based). These algorithms were investigated in two scenarios when the number of clusters is either fixed or adaptively determined. Performances of the clustering algorithms in terms of image classification and retrieval are evaluated using three publically available image databases. The evaluations have revealed that a local DCT colour-texture feature was overall the best due to its robust integration of colour and texture information. In addition, our investigation into the behaviour of different clustering algorithms has shown that each algorithm had its own strengths and limitations in segmenting local features that affect the performance of image retrieval due to variations in visual colour and texture of the images. There is no algorithm that can outperform the others using either an adaptively determined or big fixed number of clusters.
The second focus of this research is to investigate how to combine the positive effects of various local features obtained from different clustering algorithms in a fusion scheme aiming to bring about improved retrieval results over those by using a single clustering algorithm. The proposed fusion scheme integrates effectively the information from different sources, increasing the overall accuracy of retrieval. The proposed multi-evidence fusion scheme regards scores of image retrieval that are obtained from normalizing distances of applying different clustering algorithms to different types of local features as evidence and was presented in three forms: 1) evidence fusion using fixed weights (MEFS) where the weights were determined empirically and fixed a prior; 2) evidence fusion based on adaptive weights (AMEFS) where the fusion weights were adaptively determined using linear regression; 3) evidence fusion using a linear combination (Comb SUM) without weighting the evidences. Overall, all three versions of the multi-evidence fusion scheme have proved the ability to enhance the accuracy of image retrieval by increasing the number of relevant images in the ranked list. However, the improvement varied across different feature-clustering combinations (i.e. image representation) and the image databases used for the evaluation.
This thesis presents an automatic method of image retrieval that can deal with natural world scenes by applying different clustering algorithms to different local features. The method achieves good accuracies of 85% at Top 5 and 80% at Top 10 over the WANG database, which are better when compared to a number of other well-known solutions in the literature. At the same time, the knowledge gained from this research, such as the effects of different types of local features and clustering methods on the retrieval results, enriches the understanding of the field and can be beneficial for the CBIR community
Exploiting similarities between secret and cover images for improved embedding efficiency and security in digital steganography
No full textThe rapid advancements in digital communication technology and huge increase in computer power have generated an exponential growth in the use of the Internet for various commercial, governmental and social interactions that involve transmission of a variety of complex data and multimedia objects. Securing the content of sensitive as well as personal transactions over open networks while ensuring the privacy of information has become essential but increasingly challenging. Therefore, information and multimedia security research area attracts more and more interest, and its scope of applications expands significantly. Communication security mechanisms have been investigated and developed to protect information privacy with Encryption and Steganography providing the two most obvious solutions. Encrypting a secret message transforms it to a noise-like data which is observable but meaningless, while Steganography conceals the very existence of secret information by hiding in mundane communication that does not attract unwelcome snooping. Digital steganography is concerned with using images, videos and audio signals as cover objects for hiding secret bit-streams. Suitability of media files for such purposes is due to the high degree of redundancy as well as being the most widely exchanged digital data. Over the last two decades, there has been a plethora of research that aim to develop new hiding schemes to overcome the variety of challenges relating to imperceptibility of the hidden secrets, payload capacity, efficiency of embedding and robustness against steganalysis attacks. Most existing techniques treat secrets as random bit-streams even when dealing with non-random signals such as images that may add to the toughness of the challenges.This thesis is devoted to investigate and develop steganography schemes for embedding secret images in image files. While many existing schemes have been developed to perform well with respect to one or more of the above objectives, we aim to achieve optimal performance in terms of all these objectives. We shall only be concerned with embedding secret images in the spatial domain of cover images.
The main difficulty in addressing the different challenges stems from the fact that the act of embedding results in changing cover image pixel values that cannot be avoided, although these changes may not be easy to detect by the human eye. These pixel changes is a consequence of dissimilarity between the cover LSB plane and the secretimage bit-stream, and result in changes to the statistical parameters of stego-image bit-planes as well as to local image features. Steganalysis tools exploit these effects to model targeted as well as blind attacks. These challenges are usually dealt with by randomising the changes to the LSB, using different/multiple bit-planes to embed one or more secret bits using elaborate schemes, or embedding in certain regions that are noise-tolerant. Our innovative approach to deal with these challenges is first to develop some image procedures and models that result in increasing similarity between the cover image LSB plane and the secret image bit-stream. This will be achieved in two novel steps involving manipulation of both the secret image and the cover image, prior to embedding, that result a higher 0:1 ratio in both the secret bit-stream and the cover pixels‘ LSB plane.
For the secret images, we exploit the fact that image pixel values are in general neither uniformly distributed, as is the case of random secrets, nor spatially stationary. We shall develop three secret image pre-processing algorithms to transform the secret image bit-stream for increased 0:1 ratio. Two of these are similar, but one in the spatial domain and the other in the Wavelet domain. In both cases, the most frequent pixels are mapped onto bytes with more 0s. The third method, process blocks by subtracting their means from their pixel values and hence reducing the require number of bits to represent these blocks. In other words, this third algorithm also reduces the length of the secret image bit-stream without loss of information. We shall demonstrate that these algorithms yield a significant increase in the secret image bit-stream 0:1 ratio, the one that based on the Wavelet domain is the best-performing with 80% ratio.For the cover images, we exploit the fact that pixel value decomposition schemes, based on Fibonacci or other defining sequences that differ from the usual binary scheme, expand the number of bit-planes and thereby may help increase the 0:1 ratio in cover image LSB plane. We investigate some such existing techniques and demonstrate that these schemes indeed lead to increased 0:1 ratio in the corresponding cover image LSB plane. We also develop a new extension of the binary decomposition scheme that is the best-performing one with 77% ratio.
We exploit the above two steps strategy to propose a bit-plane(s) mapping embedding technique, instead of bit-plane(s) replacement to make each cover pixel usable for secret embedding. This is motivated by the observation that non-binary pixel decomposition schemes also result in decreasing the number of possible patterns for the three first bit-planes to 4 or 5 instead of 8. We shall demonstrate that the combination of the mapping-based embedding scheme and the two steps strategy produces stego-images that have minimal distortion, i.e. reducing the number of the cover pixels changes after message embedding and increasing embedding efficiency. We shall also demonstrate that these schemes result in reasonable stego-image quality and are robust against all the targeted steganalysis tools but not against the blind SRM tool.
We shall finally identify possible future work to achieve robustness against SRM at some payload rates and further improve stego-image quality
Emotion recognition from speech: tools and challenges
No full textHuman emotion recognition from speech is studied frequently for its importance in many applications, e.g. human-computer interaction. There is a wide diversity and non-agreement about the basic emotion or emotion-related states on one hand and about where the emotion related information lies in the speech signal on the other side. These diversities motivate our investigations into extracting Meta-features using the PCA approach, or using a non-adaptive random projection RP, which significantly reduce the large dimensional speech feature vectors that may contain a wide range of emotion related information. Subsets of Meta-features are fused to increase the performance of the recognition model that adopts the score-based LDC classifier. We shall demonstrate that our scheme outperform the state of the art results when tested on non-prompted databases or acted databases (i.e. when subjects act specific emotions while uttering a sentence). However, the huge gap between accuracy rates achieved on the different types of datasets of speech raises questions about the way emotions modulate the speech. In particular we shall argue that emotion recognition from speech should not be dealt with as a classification problem. We shall demonstrate the presence of a spectrum of different emotions in the same speech portion especially in the non-prompted data sets, which tends to be more “natural” than the acted datasets where the subjects attempt to suppress all but one emotion. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only
OGSR: A Low Complexity Galileo Software Receiver using Orthogonal Data and Pilot Channels
No full textTo improve localisation accuracy and multipath rejection, the Galileo-OS signal offers a new modulation with efficient power distribution technique between the two data and pilot navigation components. To achieve the full benefits of this modulation, a robust acquisition and tracking methods must be deployed. For example, using two parallel correlation channels to acquire these data and pilot will gain 3dB over using a single channel acquisition correlating with either one of them. However, dual channel SW receivers cost more processing overheads. In this paper, the authors propose to orthogonalise the received data and pilot signals so to enable their acquisition in a single correlation channel bandpass sampling receiver. Our simulation results, using Simulink, prove that OGSR performance is maintained (preserving the 3dB gain) with less processing time while the implementation complexity is reduced by 50%
How did the publication of the book The Machine That Changed The World change management thinking? Exploring 25 years of lean literature
Get PDFPurpose
The purpose of this paper is to take a critical, analytical approach to explore the growth and spread of lean through the academic and practitioner community over the last twenty-five years.
Design/methodology/approach
A comprehensive and systematic review of the extant of literature of lean was undertaken. The review spans from 1988 to 2013. To enable us to effectively manage and understand the diffusion of this set of literature a database, the Lean Publications Database (LPD), was constructed.
Findings
Lean has evolved to be one of the best-known, yet fiercely debated, process improvement methodologies. It emerged during a proliferation of such methodologies in business and management literature. Lean has developed from a generic description of Toyota Production System (TPS) to a particular type of organizational and management intervention focused on best practice and process improvement methodologies.
Research limitations/implications
This paper provides the first comprehensive review of the Lean literature, from the perspective of Lean as the unit of analysis. It covers both sides of the academic debate and categories the progression of Lean from its origins as a generic description of TPS to a movement that has change management systems in many and diverse sectors.
Practical implications
This paper demonstrates how Lean research, application and thinking has evolved over 25 years from its origins in explaining the performance improvements in Japanese auto-manufacturing to a holistic value system that is applicable to all business sectors, both private and public.
Originality/value
This study is original in that provides a different perspective to that of most previous studies. In most empirical studies on Lean, the unit of analysis is the organisation. However, in this study, the unit of analysis is the Lean phenomenon itself and represents a first step to developing an underpinning theory of Lean by linking it to the theory of swift, even flow (Schmenner and Swink, 1998), as such, it of interest to academics in the field of operations management and contributes to knowledge. It is also likely to be of interest to policy makers. Considerable amounts of public money have been spent, and continue to be spent, on promoting Lean. Taxpayers and policymakers are likely to be interested in whether that expenditure is justifiable.
Twenty-five years of publications have been analysed to provide clarity around this popular approach to improvement
Exploring the experience of neuropathic pain following spinal cord injury: an interpretative phenomenological analysis study
No full textResearch exploring pain following spinal cord injury (SCI) is largely quantitative, with very little known about what it is like to live with pain after SCI. In response to inconsistencies and the dearth of qualitative literature in this area, this study investigated the lived experience of neuropathic pain (NP), following SCI. This was conducted using semi-structured interviews with 16 people living with SCI-specific NP that had been present for a minimum of three months. Eight participants were inpatients in a rehabilitation centre, aged between 23 and 82, and eight were outpatients living in the community, aged between 26 and 77. Data from each sample were analysed separately using the qualitative methodology of Interpretative Phenomenological Analysis (IPA).
For outpatients, three themes emerged: (1) the chasm between biomedical perspectives and patient needs and beliefs; (2) the battle for ultimate agency in life; and (3) the coexistence of social cohesion and social alienation. For inpatients, four themes emerged: (1) using metaphors to describe NP; (2) the spectrum of medication experience; (3) interpreting the hospital environment; and (4) thinking about the future.
The results suggest that chronic NP is experienced in a biopsychosocial manner, and should be treated in such a way. In particular, participants felt that medication was heavily relied upon by healthcare professionals, despite limited efficacy, and articulated a desire for collaborative approaches to pain-management. Issues surrounding acceptance of NP, and its social impact, were also discussed. The involvement of significant others in pain management may improve communication and psychosocial outcomes. Promoting acceptance may be effective in facilitating psychological, and social well-being. Cognitive treatment incorporated with acceptance- and mindfulnessbased interventions (MBIs) may encourage adaptive responses to, and interpretation of, pain
Future expectations for energy in the Middle East and North Africa (MENA) region
Get PDFThe importance of the energy of the Middle East and
North Africa (MENA region) to the world and the
MENA region itself stems from the fact that 5 out of
the top 10 of the major oil producers worldwide are
located in this region. In addition the five countries
(Saudi Arabia, Iran, Iraq, Kuwait, UAE and Libya)
hold 50.5% of the total world reserv
The Exercise of External Self-Determination by Indigenous Groups: The Republic of Lakotah and the Inherent Sovereignty of American Indigenous Peoples
No full textAbstract
This article examines the implications of the choice made by the Republic of Lakotah to rely on international treaty law rather than the exercise of self-determination in declaring its independence from the United States in 2007 and 2010. States have long expressed resistance towards the granting of the principle of self-determination to minorities and indigenous groups. States fear that granting this right would lead to groups taking action to secede from the state. This article considers whether state fears of secession are realistic, and whether there is, in fact, a credible claim to external self-determination under international law for indigenous groups, or whether state fears of indigenous self-determination are grounded in other issues
Performing musicians’ understanding of the terms “mental practice” and “score analysis”
Get PDFMusicians commonly speak of mental practice and score analysis in referring to strategies widely used by performers. However, these terms may not be universally understood in the same way. To address this, 89 experienced musicians were surveyed as to their views and experiences concerning mental practice and score analysis, using a mixture of closed/rating scale and open-ended questions. They were asked what they understood by these terms and what information these strategies enabled them to obtain from the score. Results suggest that mental practice and score analysis are both considered useful, though mental practice more so. Content analysis identified the main characteristics of mental practice as: occurring away from the instrument; involving several types of imagery, often in real time; and focusing on performance preparation, particularly aspects of execution and realisation. During mental practice, the score tended to function more as a memory aid, an orientation guide, and as a point of reference for interpretation. Score analysis was considered more theoretical, though still relevant for performance preparation at a range of levels from exploratory to detailed. During score analysis, information primarily increased musical understanding of the piece, and related to both structural (e.g. form, harmony) and aesthetic (e.g. tempo, phrasing) aspects. The findings are discussed in terms of the current understanding of mental practice and score analysis in the literature, and the relationship between them. Mental practice and score analysis do have similarities, such as their benefit to performance preparation, and distinctions, for instance concerning their specific aims. However, they may be best considered as lying on a continuum of strategies for performance practice and enhancement, rather than as two distinct behaviors
Living with chronic neuropathic pain after spinal cord injury: an interpretative phenomenological analysis of community experience.
No full textPurpose: This article presents an in-depth, idiographic study examining the lived experience of chronic pain following spinal cord injury (SCI). Neuropathic pain (NP) occurs in a large majority of the SCI population and is particularly intractable to treatment. It can be both psychologically and physically debilitating. This study examines how the experience of NP is mediated by its meaning to the sufferer. Methods: Semi-structured interviews were conducted with eight people with SCI and chronic NP, attending outpatient clinics at a specialist SCI Centre in the UK. Verbatim transcripts were subjected to interpretative phenomenological analysis to further understand the experience. Results: Analysis suggested that NP has powerful consequences upon the sufferer's physical, psychological and social well-being, in line with a biopsychosocial understanding of pain. Three super-ordinate themes were identified: a perceived gap between treatments received and participants' views of what they wanted and needed; a fight for life control and acceptance; and feeling understood by others with SCI, but isolated from the non-understanding able-bodied. Conclusions: The results are discussed in terms of the possible application of acceptance-based therapy to NP and the potential for the alleviation of the debilitating consequences of NP. Implications for Rehabilitation Chronic NP after SCI is often described as worse than the injury itself, often impacting upon the sufferers physical and psychological health. The experiences of persons with SCI-specific NP highlight the impact of pain on their physical, psychological and social health. This indicates that healthcare professionals should incorporate a biopsychosocial approach for managing pain post-SCI. Routine clinical follow-up of SCI patients with chronic NP, as well as comprehensive pain management treatment programmes, could address the three themes evidenced in the current study, by moving routine intervention with NP away from pain relief, towards pain management. Continued education for patients, friends, family members and healthcare professionals may be beneficial in promoting understanding and awareness of NP and its consequences following SCI