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Full-Text Articles in Physical Sciences and Mathematics
Plenary: Nonparametric Hypothesis Testing For A Spatial Signal, Noel A. Cressie
Plenary: Nonparametric Hypothesis Testing For A Spatial Signal, Noel A. Cressie
Professor Noel Cressie
Summary form only given. Nonparametric hypothesis testing for a spatial signal can involve a large number of hypotheses. For instance, two satellite images of the same scene, taken before and after an event, could be used to test a hypothesis that the event has no environmental impact. This is equivalent to testing that the mean difference of "after-before" is zero at each of the (typically thousands of) pixels that make up the scene. In such a situation, conventional testing procedures that control the overall Type I error deteriorate as the number of hypotheses increase. Powerful testing procedures are needed for …
Texture Analysis Using Partially Ordered Markov Models, Jennifer Davidson, Ashit Talukder, Noel A. Cressie
Texture Analysis Using Partially Ordered Markov Models, Jennifer Davidson, Ashit Talukder, Noel A. Cressie
Professor Noel Cressie
Texture is a phenomenon in image data that continues to receive wide-spread interest due to its broad range of applications. The paper focuses on but one of several ways to model textures, namely, the class of stochastic texture models. the authors introduce a new spatial stochastic model called partially ordered Markov models, or POMMs. They show how POMMs are a generalization of a class of models called Markov mesh models, or MMMs, that allow an explicit closed form of the joint probability, just as do MMMs. While POMMs are a type of Markov random field model (MRF), the general MRFs …
Models And Inference For Clustering Of Locations Of Mines And Minelike Objects, Noel A. Cressie, Andrew B. Lawson
Models And Inference For Clustering Of Locations Of Mines And Minelike Objects, Noel A. Cressie, Andrew B. Lawson
Professor Noel Cressie
Mines and mine-like objects are distributed throughout an area of interest. Remote sensing of the area form an aircraft yields image data that represent the superposition of electromagnetic emissions from the mines and mine-like objects. In this article we build a hierarchical statistical model for the reconstruction of mien locations given a point pattern of the superposition of mines and mine-like objects. It is shown how inference on the mine locations can be obtained using Markov chain Monte Carlo methods.
Bayesian Hierarchical Analysis Of Minefield Data, Noel A. Cressie, Andrew B. Lawson
Bayesian Hierarchical Analysis Of Minefield Data, Noel A. Cressie, Andrew B. Lawson
Professor Noel Cressie
Based on remote sensing of a potential minefield, point locations are identified, some of which may not be mines. The mines and mine-like objects are to be distinguished based on their point patterns, although it must be emphasized that all we see is the superposition of their locations. In this paper, we construct a hierarchical spatial point-process model that accounts for the different patterns of mines and mine-like objects and uses posterior analysis to distinguish between them. Our Bayesian approach is applied to COBRA image data obtained from the NSWC Coastal Systems Station, Dahlgren Division, Panama City, Florida. 2003 Copyright …
Data Mining Of Misr Aerosol Product Using Spatial Statistics, Tao Shi, Noel A. Cressie
Data Mining Of Misr Aerosol Product Using Spatial Statistics, Tao Shi, Noel A. Cressie
Professor Noel Cressie
In climate models, aerosol forcing is the major source of uncertainty in climate forcing, over the industrial period. To reduce this uncertainty, instruments on satellites have been put in place to collect global data. However, missing and noisy observations impose considerable difficulties for scientists researching global aerosol distribution, aerosol transportation, and comparisons between satellite observations and global-climate-model outputs. In this paper, we propose a Spatial Mixed Effects (SME) statistical model to predict the missing values, denoise the observed values, and quantify the spatial-prediction uncertainties. The computations associated with the SME model are linear scalable to the number of data points, …
Mine Boundary Detection Using Partially Ordered Markov Models, Xia Hua, Jennifer Davidson, Noel A. Cressie
Mine Boundary Detection Using Partially Ordered Markov Models, Xia Hua, Jennifer Davidson, Noel A. Cressie
Professor Noel Cressie
Detection of objects in images in an automated fashion is necessary for many applications, including automated target recognition. In this paper, we present results of an automated boundary detection procedure using a new subclass of Markov random fields (MRFs), called partially ordered Markov models (POMMs). POMMs offer computational advantages over general MRFs. We show how a POMM can model the boundaries in an image. Our algorithm for boundary detection uses a Bayesian approach to build a posterior boundary model that locates edges of objects having a closed loop boundary. We apply our method to images of mines with very good …
A Spatial-Temporal Statistical Approach To Command And Control Problems In Battle-Space Digitization, David A. Wendt, Noel A. Cressie, Gardar Johannesson
A Spatial-Temporal Statistical Approach To Command And Control Problems In Battle-Space Digitization, David A. Wendt, Noel A. Cressie, Gardar Johannesson
Professor Noel Cressie
There are considerable difficulties in the integration, visualization, and overall management of battle-space information for the purpose of Command and Control (C2). One problem that we see as being important is the timely combination of digital information from multiple (possibly disparate) sources in a dynamically evolving environment. That is, there is a need to assimilate incoming data rapidly, so as to provide the battle commander with up-to-date knowledge about the battle-space and thereby to facilitate the command-decision process. In this paper, we present a spatial-temporal approach to obtaining accurate estimates of the constantly changing battlefield, based on noisy data from …
Deep Sea Underwater Robotic Exploration In The Ice-Covered Arctic Ocean With Auvs, Clayton Kunz, Chris Murphy, Richard Camilli, Hanumant Singh, John Bailey, Ryan M. Eustice, Chris Roman, Michael Jakuba, Claire Willis, Taichi Sato, Ko-Ichi Nakamura, Robert A. Sohn
Deep Sea Underwater Robotic Exploration In The Ice-Covered Arctic Ocean With Auvs, Clayton Kunz, Chris Murphy, Richard Camilli, Hanumant Singh, John Bailey, Ryan M. Eustice, Chris Roman, Michael Jakuba, Claire Willis, Taichi Sato, Ko-Ichi Nakamura, Robert A. Sohn
Christopher N. Roman
The Arctic seafloor remains one of the last unexplored areas on Earth. Exploration of this unique environment using standard remotely operated oceanographic tools has been obstructed by the dense Arctic ice cover. In the summer of 2007 the Arctic Gakkel Vents Expedition (AGAVE) was conducted with the express intention of understanding aspects of the marine biology, chemistry and geology associated with hydrothermal venting on the section of the mid-ocean ridge known as the Gakkel Ridge. Unlike previous research expeditions to the Arctic the focus was on high resolution imaging and sampling of the deep seafloor. To accomplish our goals we …
Terrain Constrained Stereo Correspondence, Gabrielle Inglis, Chris Roman
Terrain Constrained Stereo Correspondence, Gabrielle Inglis, Chris Roman
Christopher N. Roman
There is a persistent need in the oceanographic community for accurate three dimensional reconstructions of seafloor structures. To meet this need underwater mapping techniques have expanded to include the use of stereo vision and high frequency multibeam sonar for mapping scenes 10's to 100's of square meters in size. Both techniques have relative advantages and disadvantages that depend on the task at hand and the desired accuracy. In this paper, we develop a method to constrain the often problematic stereo correspondence search to small sections of the image that correspond to estimated ranges along the epipolar lines calculated from coregistered …
Application Of Structured Light Imaging For High Resolution Mapping Of Underwater Archaeological Sites, Chris Roman, Gabrielle Inglis, James Rutter
Application Of Structured Light Imaging For High Resolution Mapping Of Underwater Archaeological Sites, Chris Roman, Gabrielle Inglis, James Rutter
Christopher N. Roman
This paper presents results from recent work using structured light laser profile imaging to create high resolution bathymetric maps of underwater archaeological sites. Documenting the texture and structure of submerged sites is a difficult task and many applicable acoustic and photographic mapping techniques have recently emerged. This effort was completed to evaluate laser profile imaging in comparison to stereo imaging and high frequency multibeam mapping. A ROV mounted camera and inclined 532 nm sheet laser were used to create profiles of the bottom that were then merged into maps using platform navigation data. These initial results show very promising resolution …
P2cp: A New Cloud Storage Model To Enhance Performance Of Cloud Services, Zhe Sun, Jun Shen, Ghassan Beydoun
P2cp: A New Cloud Storage Model To Enhance Performance Of Cloud Services, Zhe Sun, Jun Shen, Ghassan Beydoun
Associate Professor Ghassan Beydoun
This paper presents a storage model named Peer to Cloud and Peer (P2CP). Assuming that the P2CP model follows the Poisson process or Little’s law, we prove that the speed and availability of P2CP is generally better than that of the pure Peer to Peer (P2P) model, the Peer to Server, Peer (P2SP) model or the cloud model. A key feature of our P2CP is that it has three data transmission tunnels: the cloud-user data transmission tunnel, the clients’ data transmission tunnel, and the common data transmission tunnel. P2CP uses the cloud storage system as a common storage system. When …
Evaluating Usage Of Wsmo And Owl-S In Semantic Web Services, Lina Azleny Kamaruddin, Jun Shen, Ghassan Beydoun
Evaluating Usage Of Wsmo And Owl-S In Semantic Web Services, Lina Azleny Kamaruddin, Jun Shen, Ghassan Beydoun
Associate Professor Ghassan Beydoun
Applying ontologies is the most promising approach to semantically enrich Web services. To facilitate this, two efforts contributed the most in enabling the creation of ontologies: OWL-S from the US and WSMO in Europe. These two compete and promote their ontologies from the design perspective, reflecting their inventors’ bias but not offering much help to Web service developers using them. To bypass existing biases and enable evaluation of ontologies expressed in these two languages, this paper provides a study of the two important facilitators, OWL-S and WSMO, surveying their usage in several SWS Projects and identifying their respective and outstanding …
Perceived Similarity And Visual Descriptions In Content-Based Image Retrieval, Yuan Zhong, Lei Ye, Wanqing Li, Philip Ogunbona
Perceived Similarity And Visual Descriptions In Content-Based Image Retrieval, Yuan Zhong, Lei Ye, Wanqing Li, Philip Ogunbona
Professor Philip Ogunbona
The use of low-level feature descriptors is pervasive in content-based image retrieval tasks and the answer to the question of how well these features describe users’ intention is inconclusive. In this paper we devise experiments to gauge the degree of alignment between the description of target images by humans and that implicitly provided by low-level image feature descriptors. Data was collected on how humans perceive similarity in images. Using images judged by humans to be similar, as ground truth, the performance of some MPEG-7 visual feature descriptors were evaluated. It is found that various descriptors play different roles in different …
Emotional States Control For On-Line Game Avatars, Ce Zhan, Wanqing Li, Farzad Safaei, Philip Ogunbona
Emotional States Control For On-Line Game Avatars, Ce Zhan, Wanqing Li, Farzad Safaei, Philip Ogunbona
Professor Philip Ogunbona
Although detailed animation has already been achieved in a number of Multi-player On-line Games (MOGs), players have to use text commands to control emotional states of avatars. Some systems have been proposed to implement a real-time automatic system facial expression recognition of players. Such systems can then be used to control avatars emotional states by driving the MOG's "animation engine" instead of text commands. Some of the challenges of such systems is the ability to detect and recognize facial components from low spatial resolution face images. In this paper a system based on an improved face detection method of Viola …
Modelling Of Color Cross-Talk In Cmos Image Sensors, Wanqing Li, Philip Ogunbona, Yan Shi, Igor Kharitonenko
Modelling Of Color Cross-Talk In Cmos Image Sensors, Wanqing Li, Philip Ogunbona, Yan Shi, Igor Kharitonenko
Professor Philip Ogunbona
This paper presents a way to model the cross-talk effect in CMOS image sensors. Two algorithms are derived from the model; both of them work on the Bayer raw data and have low computational complexity. Experiments on Macbeth color chart and real images have shown the effectiveness of the modeling to eliminate the cross-talk effect and produce better quality images with traditional color interpolation and correction algorithms designed for CCD image sensors.
Application Of Visual Modelling In Image Restoration And Colour Image Processing, Aziz Qureshi, Philip Ogunbona
Application Of Visual Modelling In Image Restoration And Colour Image Processing, Aziz Qureshi, Philip Ogunbona
Professor Philip Ogunbona
This paper describes the application of human visual models in (i) defining a visually uniform colour representation space and (ii) the formulation of visually weighted Kalman filtering for image restoration. The former being useful in colour image quantisation and compression. For (i), the uniformity of chromaticity differences at the ouptut of Frei ’s colour vision model [3] is tested and compensated for by using MacAdam’s uniform chromaticity space. For (ii), the dynamical image model of the Kalman filter is visually weighted using the frequency response of Stockham’s model [l] of human vision.
Channel-Optimized Vector Trellis Source Coding For The Awgn Channel, Philip Secker, Philip Ogunbona
Channel-Optimized Vector Trellis Source Coding For The Awgn Channel, Philip Secker, Philip Ogunbona
Professor Philip Ogunbona
A channel-optimised (joint source and channel) trellis source coder is designed for the AWGN channel. The optimum decoder is a non-linear function of the real channel information. The extension to 2D vector alphabets coupled with modifications to the signal space are found to improve performance. Favourable comparisons are made against a trellis source coder/TCM system.
Visual Perceptual Process Model And Object Segmentation, Wanqing Li, P. Ogunbona, Lei Ye, Igor Kharitonenko
Visual Perceptual Process Model And Object Segmentation, Wanqing Li, P. Ogunbona, Lei Ye, Igor Kharitonenko
Professor Philip Ogunbona
Modeling human visual process is crucial for automatic object segmentation that is able to produce consistent results to human perception. Based on the latest understanding of how human performs the task of extracting objects from images, we proposed a graph-based computational framework to model the visual process. The model supports the hierarchical nature of human visual perception and consists of the key steps of human visual perception including pre-attentive (pre-constancy) grouping, figure-and-ground organization, and attentive (post-constancy) grouping. A divide-and-conquer implementation of the model based on the concept of shortest spanning tree (SST) has demonstrated the potential of the model for …
Industrial Computer Vision Using Undefined Feature Extraction, Phil Evans, John A. Fulcher, Philip Ogunbona
Industrial Computer Vision Using Undefined Feature Extraction, Phil Evans, John A. Fulcher, Philip Ogunbona
Professor Philip Ogunbona
This paper presents an application of computer The implementation and operation of the system is vision in a real-world uncontrolled environment found at BHP Steel Port Kembla. The task is visual identification of torpedo ladles at a Blast Furnace wlahdilceh. is achieved by reading numbers attached to each 3. IMPLEMENTATION Number recognition is achieved through use of feature extraction using a Multi-Layer Perceptron (MLP) Artificial Neural Network (ANN). The novelty in the method used in this application is that the features the MLP is being trained to extract are undefined before the MLP is initialised. The results of the MLP …
Kernel Pca Of Hog Features For Posture Detection, Peng Cheng, Wanqing Li, Philip Ogunbona
Kernel Pca Of Hog Features For Posture Detection, Peng Cheng, Wanqing Li, Philip Ogunbona
Professor Philip Ogunbona
Motivated by the non-linear manifold learning ability of the Kernel Principal Component Analysis (KPCA), we propose in this paper a method for detecting human postures from single images by employing KPCA to learn the manifold span of a set of HOG features that can effectively represent the postures. The main contribution of this paper is to apply the KPCA as a non-linear learning and open-set classification tool, which implicitly learns a smooth manifold from noisy data that scatter over the feature space. For a new instance of HOG feature, its distance to the manifold that is measured by its reconstruction …
On Multiple Watermarking, Nicholas Paul Sheppard, Reihaneh Safavi-Naini, Philip Ogunbona
On Multiple Watermarking, Nicholas Paul Sheppard, Reihaneh Safavi-Naini, Philip Ogunbona
Professor Philip Ogunbona
Mintzer and Braudaway once asked: If one watermark is good, are more better? In this paper, we discuss some techniques for embedding multiple watermarks into a single multimedia object and report some observations on implementations of these techniques.
Methods Of Channel-Optimised Trellis Source Coding For The Awgn Channel, Philip Secker, Philip Ogunbona
Methods Of Channel-Optimised Trellis Source Coding For The Awgn Channel, Philip Secker, Philip Ogunbona
Professor Philip Ogunbona
Improvements to channel-optimised trellis source coding for the AWGN channel are obtained by using, in various forms, real or ‘soft’ channel information. The proposed 1 bit/sample systems use a channel-optimised encoder matched to 1) a simple decision feedback detector, 2) an expanded codebook with 2-bit quantized information and 3) an optimum non-linear estimator decoder. The third system is further improved by considering vector alphabets and both constant and average energy constrained 2D signal constellations.
Human Detection Based On Weighted Template Matching, Duc Thanh Nguyen, Philip Ogunbona, Wanqing Li
Human Detection Based On Weighted Template Matching, Duc Thanh Nguyen, Philip Ogunbona, Wanqing Li
Professor Philip Ogunbona
This paper proposes a new two-stage human detection method involving matching and verification. A Bayesian framework is developed to verify the matching score obtained from a weighted distance measure. Performance evaluation indicates that the proposed method is able to utilize the flexible matching scheme and produce superior true positive, true negative and low misclassification rates.
Compression Performance Of Jpeg Encryption Scheme, C. Kailasanathan, R. Safavi-Naini, P. Ogunbona
Compression Performance Of Jpeg Encryption Scheme, C. Kailasanathan, R. Safavi-Naini, P. Ogunbona
Professor Philip Ogunbona
Recent development in the Internet and Web based technologies require faster communication of multimedia data in a secure form. A number of encryption schemes for MPEG have been proposed. In this paper, we evaluate the compression performance of JPEG which has been encrypted with the zig-zag permutation algorithm, suggest a security enhancement to the scheme, and propose an alternative to entropy coding recommended by JPEG to compensate for the compression drop occurring due to permutation.
Image Compression Based On Genealogical Relation Of The Tsvq Indices, Jamshid Shanbehzadeh, Philip Ogunbona, Abdoihosein Sarafzadeh
Image Compression Based On Genealogical Relation Of The Tsvq Indices, Jamshid Shanbehzadeh, Philip Ogunbona, Abdoihosein Sarafzadeh
Professor Philip Ogunbona
The indices obtained by tree-structured vector quantisation (TSVQ) have an interesting property that enables them to give information about the correlation between two image blocks. Iftwo image blocks are highly correlated, they may have an identical index, or the same ancestors. The existence of high inter-block correlation in natural images results in having neighboring blocks with the same genealogy. This characteristic can be used to compress the indices. This paper introduces a novel method to exploit the genealogical relation between the image block indices obtained from a TSVQ. The performance of this scheme in terms of PSNR versus average rate …
An Audio Representation For Content Based Retrieval, Kathy Melih, Ruben Gonzalez, Philip Ogunbona
An Audio Representation For Content Based Retrieval, Kathy Melih, Ruben Gonzalez, Philip Ogunbona
Professor Philip Ogunbona
Despite: the increasing interest in multimedia data retrieval audio data has received little attention. This is due, not to a lack of interest but rather to unique difficulties posed by the medium. In particular existing unstructured audio representations do not easily lend themselves to content based retrieval and especially browsing. This paper aims to address hs oversight by developing an audio representation that provides direct support for browsing and content based retrieval. This support is the result of a structured representation based on psychoacoustic ptincip1.e~in which salient attributes of audio are directly accessible. In addition, the representation is compact thus …
An Mpeg Tolerant Authentication System For Video Data, Takeyuki Uehara, R. Safavi-Naini, P. Ogunbona
An Mpeg Tolerant Authentication System For Video Data, Takeyuki Uehara, R. Safavi-Naini, P. Ogunbona
Professor Philip Ogunbona
We propose a secure video authentication algorithm that is tolerant to visual degradation due to MPEG lossy compression to a designed level. The authentication process generates a tag that is sent with video data and the level of protection can be adjusted so that longer tags are used for higher security, and that the protection is distributed such that higher security is provided for regions of interest in the image. The computation required for authentication and verification can be largely performed as part of MPEG compression and so generation and verification of the tag can be integrated into the compression …
Human Detection Using Local Shape And Non-Redundant Binary Patterns, Duc Thanh Nguyen, Wanqing Li, Philip Ogunbona
Human Detection Using Local Shape And Non-Redundant Binary Patterns, Duc Thanh Nguyen, Wanqing Li, Philip Ogunbona
Professor Philip Ogunbona
Motivated by the advantages of using shape matching technique in detecting objects in various postures and viewpoints and the discriminative power of local patterns in object recognition, this paper proposes a human detection method combining both shape and appearance cues. In particular, local shapes of the body parts are detected using template matching. Based on body parts' shapes, local appearance features are extracted. We introduce a novel local binary pattern (LBP) descriptor, called Non-Redundant LBP (NRLBP), to encode local appearance of human. The proposed method was evaluated and compared with other state-of-the-art human detection methods on two commonly used datasets: …
Image Content Annotation Based On Visual Features, Lei Ye, Philip Ogunbona, J. Wang
Image Content Annotation Based On Visual Features, Lei Ye, Philip Ogunbona, J. Wang
Professor Philip Ogunbona
Automatic image content annotation techniques attempt to explore structural visual features of images that describe image content and associate them with image semantics. In this paper, two types of concept spaces, atomic concept and collective concept spaces, are defined and the annotation problems in those spaces are formulated as feature classification and Bayesian inference, respectively. A scheme of image content annotation in this framework is presented and evaluated as an application of photo categorization using MPEG-7 VCE2 dataset and its ground truth. The experimental results show a promising performance.
Edge Image Description Using Fractal Interpolation, P Motallebi, P O. Ogunbona
Edge Image Description Using Fractal Interpolation, P Motallebi, P O. Ogunbona
Professor Philip Ogunbona
Edge images derived from compressed image databases are described using fractal techniques. The proposed method is able to give affine transformation-invariant description suitable for use in a query-by-example database application. Comparison among the proposed method, polynomial interpolation and spline interpolation is given. It is concluded that fractal interpolation can give a compact description of image contours and is able to cope with random perturbation of the coordinates of the contour points by as much as 25 percent.