Order statistic filters for image matching

The rank and census are two filters based on order statistics which have been applied to the image matching problem for stereo pairs. Advantages of these filters include their robustness to radiometric distortion and small amounts of random noise, and their amenability to hardware implementation. In this paper, a new matching algorithm is presented, which provides an overall framework for matching, and is used to compare the rank and census techniques with standard matching metrics. The algorithm was tested using both real stereo pairs and a synthetic pair with ground truth. The rank and census filters were shown to significantly improve performance in the case of radiometric distortion. In all cases, the results obtained were comparable to, if not better than, those obtained using standard matching metrics. Furthermore, the rank and census have the additional advantage that their computational overhead is less than these metrics. For all techniques tested, the difference between the results obtained for the synthetic stereo pair, and the ground truth results was small.

The application of the parallel track model in community health promotion : a literature review

The parallel track model is one of the several models that are used in health promotion programmes that focus on community empowerment. It is unique in that it explicitly incorporates an empowerment approach with a top-down health programme. Since its development in 1999-2000 the model has been used in various health programmes in both developed and developing countries. The aim of this review is to examine the nature and extent of the application of this model and its contribution to promoting health. A review of the literature published between 2000 and 2011 was conducted. Nine results matched the inclusion criteria and revealed that the model has been mostly applied to disadvantaged communities to address health determinants, such as poverty and health literacy. This review found that the model had a positive impact on specific health outcomes such as health literacy and community capacity. We concluded that the parallel track model has the most potential for building capacity for community health promotion and appears to be the least useful for interventions focusing on health behaviour change within a limited time frame.

Image-based flow visualisation (IBFV) to enhance interpretation of complex flow patterns within a shallow tidal barrier estuary

We applied a texture-based flow visualisation technique to a numerical hydrodynamic model of the Pumicestone Passage in southeast Queensland, Australia. The quality of the visualisations using our flow visualisation tool, are compared with animations generated using more traditional drogue release plot and velocity contour and vector techniques. The texture-based method is found to be far more effective in visualising advective flow within the model domain. In some instances, it also makes it easier for the researcher to identify specific hydrodynamic features within the complex flow regimes of this shallow tidal barrier estuary as compared with the direct and geometric based methods.

The image of the Hungarian and UK building industries : a comparative analysis

Concern that poor image of UK construction industry is restricting recruitment has lead to call for action. This paper gives the results of a recent comparative analysis of the image of both UK and Hungarian industries which indicates the UK image to be relatively good. The perceived cause of Hungarian problems is the poor level of organisation and management.

Image based visual servo control for fixed wing UAVs tracking linear infrastructure in wind

This paper presents an Image Based Visual Servo control design for Fixed Wing Unmanned Aerial Vehicles tracking locally linear infrastructure in the presence of wind using a body fixed imaging sensor. Visual servoing offers improved data collection by posing the tracking task as one of controlling a feature as viewed by the inspection sensor, although is complicated by the introduction of wind as aircraft heading and course angle no longer align. In this work it is shown that the effects of wind alter the desired line angle required for continuous tracking to equal the wind correction angle as would be calculated to set a desired course. A control solution is then sort by linearizing the interaction matrix about the new feature pose such that kinematics of the feature can be augmented with the lateral dynamics of the aircraft, from which a state feedback control design is developed. Simulation results are presented comparing no compensation, integral control and the proposed controller using the wind correction angle, followed by an assessment of response to atmospheric disturbances in the form of turbulence and wind gusts

The use of a Riesz fractional differential-based approach for texture enhancement in image processing

Abstract: Texture enhancement is an important component of image processing, with extensive application in science and engineering. The quality of medical images, quantified using the texture of the images, plays a significant role in the routine diagnosis performed by medical practitioners. Previously, image texture enhancement was performed using classical integral order differential mask operators. Recently, first order fractional differential operators were implemented to enhance images. Experiments conclude that the use of the fractional differential not only maintains the low frequency contour features in the smooth areas of the image, but also nonlinearly enhances edges and textures corresponding to high-frequency image components. However, whilst these methods perform well in particular cases, they are not routinely useful across all applications. To this end, we applied the second order Riesz fractional differential operator to improve upon existing approaches of texture enhancement. Compared with the classical integral order differential mask operators and other fractional differential operators, our new algorithms provide higher signal to noise values, which leads to superior image quality.

Image-based visual navigation for mobile robots

We introduce a new image-based visual navigation algorithm that allows the Cartesian velocity of a robot to be defined with respect to a set of visually observed features corresponding to previously unseen and unmapped world points. The technique is well suited to mobile robot tasks such as moving along a road or flying over the ground. We describe the algorithm in general form and present detailed simulation results for an aerial robot scenario using a spherical camera and a wide angle perspective camera, and present experimental results for a mobile ground robot.

Advertising and promotion : an integrated marketing communications perspective

This text explores the area of advertising and promotion practice. It shows how real organisations coordinate the various elements of the promotional mix with other marketing activities."--Provided by publisher

Evaluation in health outcomes research : linking theories, methodologies and practice in health promotion.

Health outcomes research has developed as a means of evaluating the effectiveness of health care interventions and as an approach to informing resource allocation. The use of a health outcomes approach in health promotion has made increasing demands on evaluation methodologies to demonstrate program effectiveness. However, criticism of the contribution of health promotion to outcomes research has made several assumptions about the use of qualitative methodologies and the content of program objectives largely derived from a biomedical approach. In contrast to the measurement of biomedical interventions in clinical health care, health promotion practice involves social phenomena, wide-reaching cultural, psychological, political and ideological problems and issues. The integration of methodologies of health promotion evaluation will inform further conceptualisation of the health outcomes approach with the differentiation of three types of outcomes: health development outcomes; social health outcomes; and biomedical health outcomes. It is concluded that this differentiation moves away from dualist concepts that advocate the replacement of goals and targets with regional and locally based approaches. Rather, the future direction for health promotion evaluation needs to employ a framework that elaborates multiple methodologies and approaches necessary for establishing what relationships exist between morbidity, mortality, health advancement and equity.

A multi-layered approach for site detection in UAS emergency landing scenarios using geometry-based image segmentation

This paper presents an alternative approach to image segmentation by using the spatial distribution of edge pixels as opposed to pixel intensities. The segmentation is achieved by a multi-layered approach and is intended to find suitable landing areas for an aircraft emergency landing. We combine standard techniques (edge detectors) with novel developed algorithms (line expansion and geometry test) to design an original segmentation algorithm. Our approach removes the dependency on environmental factors that traditionally influence lighting conditions, which in turn have negative impact on pixel-based segmentation techniques. We present test outcomes on realistic visual data collected from an aircraft, reporting on preliminary feedback about the performance of the detection. We demonstrate consistent performances over 97% detection rate.

The use of SMS messaging for physical activity promotion : preferences of Australian adolescents and their parents

OBJECTIVE: Recent increases in youth mobile phone ownership and usage may provide a unique and innovative opportunity for engagement by health promoters, via a familiar and immediately accessible medium. This study investigated adolescents’ and their parents’ preferences for promoting physical activity via means of SMS messaging. METHODS: Adolescents (36 males and 76 females) and their parents (37 males 75 females) were recruited from two non-denominational same-sex private schools, in Brisbane, Australia. The mean age and standard deviation (SD) for adolescents and parents was 14.03 (0.58) and 47.18 (4.65) respectively. Participants responded to a series of questions regarding mobile phone ownership, and preferences for physical activity, school-based physical activity programs, and programs invovling SMS messaging. Data analysis included descriptive statistics and frequency distributions. T-tests were employed to measure gender effect. RESULTS: Overall, 47 (42%) parents desired their child to be more physically active, and were interested for their child to participate in a school-based physical activity program. Of those parents, 16 (34%) parents were interested in their child participating in an SMS-based physical activity program, with 21 (45%) not interested, and 10 (21%) neutral. One hundred and four (95%) adolescents owned a mobile phone, with 84 (82%) of those adolescents wanting to be more physically active. Of those adolescents, 14 (17%) were interested in participating in an SMS-based physical activity program, with 40 (48%) not interested, and 30 (36%) neutral. There was no significant gender effect. CONCLUSIONS: Although SMS messaging may provide an innovative method for youth physical activity promotion, low levels of interest are concerning. These results differ from other studies utilising SMS messaging for the purpose of health promotion, where more positive feedback from participants were reported. A screening process to gauge interest prior to the implementation of any SMS-based health promotion program may prove invaluable toward the success of the program.

Modelling users' contextual querying behaviour for web image searching

The rapid growth of visual information on Web has led to immense interest in multimedia information retrieval (MIR). While advancement in MIR systems has achieved some success in specific domains, particularly the content-based approaches, general Web users still struggle to find the images they want. Despite the success in content-based object recognition or concept extraction, the major problem in current Web image searching remains in the querying process. Since most online users only express their needs in semantic terms or objects, systems that utilize visual features (e.g., color or texture) to search images create a semantic gap which hinders general users from fully expressing their needs. In addition, query-by-example (QBE) retrieval imposes extra obstacles for exploratory search because users may not always have the representative image at hand or in mind when starting a search (i.e. the page zero problem). As a result, the majority of current online image search engines (e.g., Google, Yahoo, and Flickr) still primarily use textual queries to search. The problem with query-based retrieval systems is that they only capture users’ information need in terms of formal queries;; the implicit and abstract parts of users’ information needs are inevitably overlooked. Hence, users often struggle to formulate queries that best represent their needs, and some compromises have to be made. Studies of Web search logs suggest that multimedia searches are more difficult than textual Web searches, and Web image searching is the most difficult compared to video or audio searches. Hence, online users need to put in more effort when searching multimedia contents, especially for image searches. Most interactions in Web image searching occur during query reformulation. While log analysis provides intriguing views on how the majority of users search, their search needs or motivations are ultimately neglected. User studies on image searching have attempted to understand users’ search contexts in terms of users’ background (e.g., knowledge, profession, motivation for search and task types) and the search outcomes (e.g., use of retrieved images, search performance). However, these studies typically focused on particular domains with a selective group of professional users. General users’ Web image searching contexts and behaviors are little understood although they represent the majority of online image searching activities nowadays. We argue that only by understanding Web image users’ contexts can the current Web search engines further improve their usefulness and provide more efficient searches. In order to understand users’ search contexts, a user study was conducted based on university students’ Web image searching in News, Travel, and commercial Product domains. The three search domains were deliberately chosen to reflect image users’ interests in people, time, event, location, and objects. We investigated participants’ Web image searching behavior, with the focus on query reformulation and search strategies. Participants’ search contexts such as their search background, motivation for search, and search outcomes were gathered by questionnaires. The searching activity was recorded with participants’ think aloud data for analyzing significant search patterns. The relationships between participants’ search contexts and corresponding search strategies were discovered by Grounded Theory approach. Our key findings include the following aspects: - Effects of users' interactive intents on query reformulation patterns and search strategies - Effects of task domain on task specificity and task difficulty, as well as on some specific searching behaviors - Effects of searching experience on result expansion strategies A contextual image searching model was constructed based on these findings. The model helped us understand Web image searching from user perspective, and introduced a context-aware searching paradigm for current retrieval systems. A query recommendation tool was also developed to demonstrate how users’ query reformulation contexts can potentially contribute to more efficient searching.

Establishing design thinking : accident, program frameworks and personal practices

Distribution through electronic media provides an avenue for promotion, recognition and an outlet of display for graphic designers. The emergence of available media technologies have enabled graphic designers to extend these boundaries of their practice. In this context the designer is constantly striving for aesthetic success and is strongly influenced by the fashion and trends of contemporary design work. The designer is always in a state of inquiry, finding pathways of discovery that lead to innovation and originality that are highly valued criteria for self-evaluation. This research is based on an analysis of the designer perspective and the processes used within an active graphic design practice specializing entirely within a digital collage domain. Contemporary design methodologies were critically examined, compared and refined to reflect the self-practice of the researcher. The refined methodology may assist designers in maintaining systematic work practices, as well as promote the importance of exploration and experimentation processes. Research findings indicate some differences in the identified methodologies and the design practice of the researcher in the sense that many contemporary designers are not confined to a client-base but are self-generating design images influenced by contemporary practitioners. As well as confirming some aspects of more conventional design processes, the researcher found that accidental discoveries and the designer’s interaction with technology plays a significant part in the design process.

Robust image hash functions using higher order spectra

Robust hashing is an emerging field that can be used to hash certain data types in applications unsuitable for traditional cryptographic hashing methods. Traditional hashing functions have been used extensively for data/message integrity, data/message authentication, efficient file identification and password verification. These applications are possible because the hashing process is compressive, allowing for efficient comparisons in the hash domain but non-invertible meaning hashes can be used without revealing the original data. These techniques were developed with deterministic (non-changing) inputs such as files and passwords. For such data types a 1-bit or one character change can be significant, as a result the hashing process is sensitive to any change in the input. Unfortunately, there are certain applications where input data are not perfectly deterministic and minor changes cannot be avoided. Digital images and biometric features are two types of data where such changes exist but do not alter the meaning or appearance of the input. For such data types cryptographic hash functions cannot be usefully applied. In light of this, robust hashing has been developed as an alternative to cryptographic hashing and is designed to be robust to minor changes in the input. Although similar in name, robust hashing is fundamentally different from cryptographic hashing. Current robust hashing techniques are not based on cryptographic methods, but instead on pattern recognition techniques. Modern robust hashing algorithms consist of feature extraction followed by a randomization stage that introduces non-invertibility and compression, followed by quantization and binary encoding to produce a binary hash output. In order to preserve robustness of the extracted features, most randomization methods are linear and this is detrimental to the security aspects required of hash functions. Furthermore, the quantization and encoding stages used to binarize real-valued features requires the learning of appropriate quantization thresholds. How these thresholds are learnt has an important effect on hashing accuracy and the mere presence of such thresholds are a source of information leakage that can reduce hashing security. This dissertation outlines a systematic investigation of the quantization and encoding stages of robust hash functions. While existing literature has focused on the importance of quantization scheme, this research is the first to emphasise the importance of the quantizer training on both hashing accuracy and hashing security. The quantizer training process is presented in a statistical framework which allows a theoretical analysis of the effects of quantizer training on hashing performance. This is experimentally verified using a number of baseline robust image hashing algorithms over a large database of real world images. This dissertation also proposes a new randomization method for robust image hashing based on Higher Order Spectra (HOS) and Radon projections. The method is non-linear and this is an essential requirement for non-invertibility. The method is also designed to produce features more suited for quantization and encoding. The system can operate without the need for quantizer training, is more easily encoded and displays improved hashing performance when compared to existing robust image hashing algorithms. The dissertation also shows how the HOS method can be adapted to work with biometric features obtained from 2D and 3D face images.