Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 19 of 19
Full-Text Articles in Physical Sciences and Mathematics
Index Factorised Image Adaptive Vector Quantisation, Jamshid Shanbehzadeh, Philip Ogunbona
Index Factorised Image Adaptive Vector Quantisation, Jamshid Shanbehzadeh, Philip Ogunbona
Professor Philip Ogunbona
No abstract provided.
Face To Face Communications In Multiplayer Online Games: A Real-Time System, Ce Zhan, Wanqing Li, Farzad Safaei, Philip Ogunbona
Face To Face Communications In Multiplayer Online Games: A Real-Time System, Ce Zhan, Wanqing Li, Farzad Safaei, Philip Ogunbona
Professor Philip Ogunbona
Multiplayer online games (MOG) bring HCI into a new era of human-human interactions in computer world. Although current MOG provide more interactivity and social interaction in the virtual world, natural facial expression as a key factor in emulating face to face communications has been neglected by game designers. In this work, we propose a real-time automatic system to recognize players’ facial expressions, so that the recognition results can be used to drive the MOG’s “facial expression engine” instead of “text commands”. Our major contributions are the evaluation, improvement and efficient implementation of existing algorithms to build a real-time system that …
Human Detection With Contour-Based Local Motion Binary Patterns, Duc Thanh Nguyen, Philip Ogunbona, Wanqing Li
Human Detection With Contour-Based Local Motion Binary Patterns, Duc Thanh Nguyen, Philip Ogunbona, Wanqing Li
Professor Philip Ogunbona
This paper presents a human detection method using contour- based local motion features. The local motion is encoded using a variant of the popular Local Binary Pattern (LBP) called Non-Redundant Local Binary Pattern (NRLBP) descriptor computed on the difference image of two consecutive frames. In addition, the local motion features are extracted along the human's boundary contour. Localising features on the contours has the advantage of utilizing a precise human shape description. A motivation of the proposed method is that most of informative movements are performed on boundary contours of the body parts, e.g. legs of pedestrians. Evaluation of the …
A Secure And Flexible Authentication System For Digital Images, Takeyuki Uehara, Reihaneh Safavi-Naini, Philip Ogunbona
A Secure And Flexible Authentication System For Digital Images, Takeyuki Uehara, Reihaneh Safavi-Naini, Philip Ogunbona
Professor Philip Ogunbona
Authentication of image data is a challenging task. Unlike data authentication systems that detect a single bit change in the data, image authentication systems must remain tolerant to changes resulting from acceptable image processing or compression algorithms while detecting malicious tampering with the image. Tolerance to the changes due to lossy compression systems is particularly important because in the majority of cases images are stored and transmitted in compressed form, and so it is important for verification to succeed if the compression is within the allowable range. In this paper we consider an image authentication system that generates an authentication …
Performance Enhancement For Fuzzy Adaptive Resonance Theory (Art) Neural Networks, Golshah Naghdy, Jiazhao Wang, Philip Ogunbona
Performance Enhancement For Fuzzy Adaptive Resonance Theory (Art) Neural Networks, Golshah Naghdy, Jiazhao Wang, Philip Ogunbona
Professor Philip Ogunbona
A modified fuzzy adaptive resonance theory neural network (ART) is used as a classifier for a texture recognition system. The system consists of a wavelet based low level feature detector and a high level ART classifier. The performance improvement is measured in terms of identification accuracy and computational burden.
Index Compressed Tree-Structured Vector Quantisation, Jamshid Shanbehzadeh, Philip Ogunbona
Index Compressed Tree-Structured Vector Quantisation, Jamshid Shanbehzadeh, Philip Ogunbona
Professor Philip Ogunbona
This paper introduces a novel coding scheme based on Tree-Structured Vector Quantisation (TSVQ) scheme for image compression. The genealogical relationship among the indices of the neighbouring blocks generated from vector quantisation is exploited to improve the coding performance of TSVQ. The proposed coding scheme provides about 3.5 dB improvement over the basic TSVQ scheme and outperforms VQ schemes with memory and JPEG coding standard at low bit-rates. In addition its performance is comparable with address VQ but with much less complexity.
Texture Analysis Using Gabor Wavelets, Golshah Naghdy, Jianli Wang, Philip Ogunbona
Texture Analysis Using Gabor Wavelets, Golshah Naghdy, Jianli Wang, Philip Ogunbona
Professor Philip Ogunbona
Receptive field profiles of simple cells in the visual cortex have been shown to resemble even- symmetric or odd-symmetric Gabor filters. Computational models employed in the analysis of textures have been motivated by two-dimensional Gabor functions arranged in a multi-channel architecture. More recently wavelets have emerged as a powerful tool for non-stationary signal analysis capable of encoding scale-space information efficiently. A multi-resolution implementation in the form of a dyadic decomposition of the signal of interest has been popularized by many researchers. In this paper, Gabor wavelet configured in a 'rosette' fashion is used as a multi-channel filter-bank feature extractor for …
Coding Gain And Spatial Localisation Properties Of Discrete Wavelet Transform Filters For Image Coding, J Andrew, P Ogunbona, F Paoloni
Coding Gain And Spatial Localisation Properties Of Discrete Wavelet Transform Filters For Image Coding, J Andrew, P Ogunbona, F Paoloni
Professor Philip Ogunbona
The authors consider coding gain and spatial localisation properties of DWT filters for still image compression. Using a JPEG type quantisation and encoding method several images are compressed using a DWT implemented using various two-band subband filter sets. It is concluded that a relatively high coding gain (relative to a highly correlated source) is necessary, but not sufficient, for good image coding performance. Further, it is observed that low spatial width filters are desirable, particularly in regard to reduced ringing distortion. In terms of the tradeoff between coding gain and spatial localisation, and in terms of actual coding performance, it …
Semi-Supervised Maximum A Posteriori Probability Segmentation Of Brain Tissues From Dual-Echo Magnetic Resonance Scans Using Incomplete Training Data, Wanqing Li, P Ogunbona, C Desilva, Y Attikiouzel
Semi-Supervised Maximum A Posteriori Probability Segmentation Of Brain Tissues From Dual-Echo Magnetic Resonance Scans Using Incomplete Training Data, Wanqing Li, P Ogunbona, C Desilva, Y Attikiouzel
Professor Philip Ogunbona
This study presents a stochastic framework in which incomplete training data are used to boost the accuracy of segmentation and to optimise segmentation when images under consideration are corrupted by inhomogeneities. The authors propose a semi-supervised maximum a posteriori probability (ssMAP) segmentation method that is able to utilise any amount of training data that are usually insufficient for supervised segmentation. The ssMAP unifies supervised and unsupervised segmentation and takes the two as its special cases. To deal with inhomogeneities, the authors propose to incorporate a bias field into the ssMAP and present an algorithm (referred to as ssMAPe) for simultaneous …
Visual Information Processing And Content Management: An Overview, Philip Ogunbona
Visual Information Processing And Content Management: An Overview, Philip Ogunbona
Professor Philip Ogunbona
Visual information processing and the management of visual content has become a significant part of contemporary economy. The visual information processing pipeline is divided into several modules including, (i) capture and enhancement, (ii) efficient representation for storage and transmission, (iii) processing for efficient and secure distribution, and, (iv) representation for efficient archiving and retrieval. Advances in semiconductor technology and optimum signal processing models and algorithms, provide tools to improve each module of the processing pipeline. Insight from other areas of study including psychology augments and informs the models being developed to understand and design efficient visual content management systems. The …
Index Compressed Image Adaptive Vector Quantisation, Jamshid Shanbehzadeh, Philip Ogunbona
Index Compressed Image Adaptive Vector Quantisation, Jamshid Shanbehzadeh, Philip Ogunbona
Professor Philip Ogunbona
This paper introduces an improved image adaptive vector quantisation technique - index compressed image adaptive vector quantisation (IC-IAVQ). Despite its advantage over the universal codebook VQ, basic image adaptive VQ (IAVQ) is still suboptimum; it neglects the correlation among block indices in the encoded image. The new technique, IC-IAVQ, overcomes this suboptimality through a pre-processing and lossless compression of block indices. Simulation results using several images show that IC-IAVQ outperforms IAVQ and entropy coded IAVQ, especially at low bit-rates by about 2dB on average.
Human Motion Simulation And Action Corpus, Gang Zheng, Wanqing Li, Philip Ogunbona, Liju Dong, Igor Kharitonenko
Human Motion Simulation And Action Corpus, Gang Zheng, Wanqing Li, Philip Ogunbona, Liju Dong, Igor Kharitonenko
Professor Philip Ogunbona
Acquisition of large scale good quality training samples is becoming a major issue in machine learning based human motion analysis. This paper presents a method to simulate continuous gross human body motion with the intention to establish a human motion corpus for learning and recognition. The simulation is achieved by a temporal-spatialtemporal decomposition of human motion into actions, joint actions and actionlets based on the human kinematic model. The actionlet models the primitive moving phase of a joint and represents the muscle movement governed by kinesiological principles. Joint actions and body actions are constructed from actionlets through constrained concatenation and …
Smoke Detection In Videos Using Non-Redundant Local Binary Pattern-Based Features, Hongda Tian, Wanqing Li, Philip Ogunbona, Duc Thanh Nguyen, Ce Zhan
Smoke Detection In Videos Using Non-Redundant Local Binary Pattern-Based Features, Hongda Tian, Wanqing Li, Philip Ogunbona, Duc Thanh Nguyen, Ce Zhan
Professor Philip Ogunbona
This paper presents a novel and low complexity method for real-time video-based smoke detection. As a local texture operator, Non-Redundant Local Binary Pattern (NRLBP) is more discriminative and robust to illumination changes in comparison with original Local Binary Pattern (LBP), thus is employed to encode the appearance information of smoke. Non-Redundant Local Motion Binary Pattern (NRLMBP), which is computed on the difference image of consecutive frames, is introduced to capture the motion information of smoke. Experimental results show that NRLBP outperforms the original LBP in the smoke detection task. Furthermore, the combination of NRLBP and NRLMBP, which can be considered …
Private Fingerprint Matching, Siamak Shahandashti, Reihaneh Safavi-Naini, Philip Ogunbona
Private Fingerprint Matching, Siamak Shahandashti, Reihaneh Safavi-Naini, Philip Ogunbona
Professor Philip Ogunbona
We propose a fully private fingerprint matching protocol that compares two fingerprints based on the most widely-used minutia-based fingerprint matching algorithm. The protocol enables two parties, each holding a private fingerprint, to find out if their fingerprints belong to the same individual. Unlike previous works, we do not make any simplifying assumption on the matching algorithm or use generic multiparty computation protocols in our constructions. We employ a commonly-used algorithm that works by first comparing minutia pairs from the two fingerprints based on their types, locations, and orientations, and then checking if the number of matching minutia pairs is more …
Illumination Invariant Face Detection Using Classifier Fusion, Alister Cordiner, Philip Ogunbona, Wanqing Li
Illumination Invariant Face Detection Using Classifier Fusion, Alister Cordiner, Philip Ogunbona, Wanqing Li
Professor Philip Ogunbona
An approach to the problem of illumination variations in face detection that uses classifier fusion is presented. Multiple face detectors are seperately trained for different illumination environments and their results are combined using a combination rule. To define the illumination environments, the training samples are clustered based on their illumination using unsupervised training. Different methods of clustering the samples and combining the outputs of the classifiers are examined. Experiments with the AR face database show that the proposed method achieves higher accuracy than the traditional monolithic face detection method.
Optimal Image Watermark Decoding, Wenming Lu, Wanqing Li, Reihaneh Safavi-Naini, Philip Ogunbona
Optimal Image Watermark Decoding, Wenming Lu, Wanqing Li, Reihaneh Safavi-Naini, Philip Ogunbona
Professor Philip Ogunbona
Not much has been done in utilizing the available information at the decoder to optimize the decoding performance of watermarking systems. This paper focuses on analyzing different decoding methods, namely, Minimum Distance, Maximum Likelihood and Maximum a-posteriori decoding given varying information at the decoder in the blind detection context. Specifically, we propose to employ Markov random fields to model the prior information given the embedded message is a structured logo. The application of these decoding methods in Quantization Index Modulation systems shows that the decoding performance can be improved by Maximum Likelihood decoding that exploits the property of the attack …
A Novel Multi-Image Query Techniques For Automatic Query Concept Capture, Fenghui Ren, Philip Ogunbona, Lei Ye
A Novel Multi-Image Query Techniques For Automatic Query Concept Capture, Fenghui Ren, Philip Ogunbona, Lei Ye
Professor Philip Ogunbona
No abstract provided.
Description Of Evolutional Changes In Image Time Sequences Using Mpeg-7 Visual Descriptors, Lei Ye, Lingzhi Cao, Philip Ogunbona, Wanqing Li
Description Of Evolutional Changes In Image Time Sequences Using Mpeg-7 Visual Descriptors, Lei Ye, Lingzhi Cao, Philip Ogunbona, Wanqing Li
Professor Philip Ogunbona
Colour and texture visual descriptors have been developed to represent structural features of images, mainly under the Query-by- Example (QBE) image retrieval paradigm. This paper explores applicability of MPEG-7 visual descriptors to describe and measure evolutional changes in image time sequences, using a fruit rotting process as an example. The research found that MPEG-7 visual descriptors can be applied to describe evolutional changes in image time sequences. The experimental results are provided using bananas captured in image time sequences. The results show the desirable monotonicity of description metrics of MPEG-7 similarity matching for image time sequences and their sensitivity to …
Region-Based Watermarking By Distribution Adjustment, Gareth Brisbane, Reihaneh Safavi-Naini, Philip Ogunbona
Region-Based Watermarking By Distribution Adjustment, Gareth Brisbane, Reihaneh Safavi-Naini, Philip Ogunbona
Professor Philip Ogunbona
No abstract provided.