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Articles 31 - 53 of 53
Full-Text Articles in Physical Sciences and Mathematics
A Part-Based Template Matching Method For Multi-View Human Detection, Duc Thanh Nguyen, Wanqing Li, Philip Ogunbona
A Part-Based Template Matching Method For Multi-View Human Detection, Duc Thanh Nguyen, Wanqing Li, Philip Ogunbona
Professor Philip Ogunbona
This paper proposes a part-based template matching method for multi-view human detection. The proposed method includes two stages: matching and verification. In particular, the best individual matching parts given a detection window are determined using an improved template matching algorithm. The hypothesis of the matched parts forming a human is then verified by employing a Bayesian-based model. The verification is not only based on the matching costs of individual parts but also how well the combining the matched parts satisfying the configuration constraints of the human body. Experimental results have shown that the proposed method is robust for detecting humans …
A Pixel-Based Robust Image Watermarking System, Wenming Lu, Wanqing Li, Rei Safavi-Naini, Philip Ogunbona
A Pixel-Based Robust Image Watermarking System, Wenming Lu, Wanqing Li, Rei Safavi-Naini, Philip Ogunbona
Professor Philip Ogunbona
Robust image watermarking systems are required to be resistant to geometric attacks in addition to common image processing tasks, such as JPEG compression. However, robustness against geometric attacks, such as rotation, scaling and translation, still remains one of the most challenging research topics in image watermarking. We propose a new pixel-based watermarking system in which a binary logo is embedded, a bit per pixel, in the pixel domain of an image. The encoder of the proposed system is based on a sliding window embedding scheme that applies the local average quantization index modulation (QIM), to achieve geometric attack robustness. The …
Similarity Measures For Compressed Image Databases, P Sangassapaviriya, Philip Ogunbona
Similarity Measures For Compressed Image Databases, P Sangassapaviriya, Philip Ogunbona
Professor Philip Ogunbona
For image database applications it is desirable that functions such as searching, browsing and partial recall be done without the need to totally decompress the image. This has the advantage of alleviating possible burden and degradation that the network may suffer. Edge images derived from wavelet-compressed images are considered as index that can be queried by example. Zernike moment invariants are used as descriptors for the index edge image and the query sketch image. The descriptions are compared for the purpose of database searching. The query images were allowed to undergo translation, rotation, scaling and some deformation. Simulation results gave …
Wavelet-Based Feature-Adaptive Adaptive Resonance Theory Neural Network For Texture Identification, Jiazhao Wang, Golshah Naghdy, Philip Ogunbona
Wavelet-Based Feature-Adaptive Adaptive Resonance Theory Neural Network For Texture Identification, Jiazhao Wang, Golshah Naghdy, Philip Ogunbona
Professor Philip Ogunbona
A new method of texture classification comprising two processing stages, namely a low-level evolutionary feature extraction based on Gabor wavelets and a high-level neural network based pattern recognition, is proposed. The design of these stages is motivated by the processes involved in the human visual system: low-level receptors responsible for early vision processing and the high-level cognition. Gabor wavelets are used as extractors of ‘‘lowlevel’’ features that feed the feature-adaptive adaptive resonance theory (ART) neural network acting as a high-level ‘‘cognitive system.’’ The novelty of the model developed in this paper lies in the use of a self-organizing input layer …
Content-Based Retrieval From Compressed-Image Databases, Philip Ogunbona, P Sangassapaviriya
Content-Based Retrieval From Compressed-Image Databases, Philip Ogunbona, P Sangassapaviriya
Professor Philip Ogunbona
There is an enormous amount of multi-media data including images, video, speech, audio and text, distributed among the various computer nodes on the Internet. The extent to which a user wiU be able to derive useful information from these data depends largely on the ease with which required data can be retrieved from the databases. The share volume of the data also poses a storage constraint on the databases; hence these data will need to exist in the compressed form on the databases. In this paper we concentrate on image data and propose a new paradigm in which a compressed …
New Feature-Based Image Adaptive Vector Quantisation Coder, Jamshid Shanbehzadeh, Philip O. Ogunbona
New Feature-Based Image Adaptive Vector Quantisation Coder, Jamshid Shanbehzadeh, Philip O. Ogunbona
Professor Philip Ogunbona
It is difficult to achieve a good low bit rate image compression performance with traditional block coding schemes such as transform coding and vector quantization, without regard for the human visual perception or signal dependency. These classical block coding schemes are based on minimizing the MSE at a certain rate. This procedure results in more bits being allocated to areas which may not be visually important and the resulting quantization noise manifests as a blocking artifact. Blocking artifacts are known to be psychologically more annoying than white noise when the human visual response is considered. While image adaptive vector quantization …
Securing Wavelet Compression With Random Permutations, Takeyuki Uehara, Reihaneh Safavi-Naini, Philip Ogunbona
Securing Wavelet Compression With Random Permutations, Takeyuki Uehara, Reihaneh Safavi-Naini, Philip Ogunbona
Professor Philip Ogunbona
Wavelet compression for digital images achieves very high compression with reasonably high image quality and so is widely used in various applications. Adding security to compression algorithms has been proposed in a number of compression systems with the aim reducing the overall cost of compression and encryption. In this paper we propose a combined compression and encryption system based on wavelet transform and examine its security. Our results show that with a relatively small added cost varying degrees of security can be obtained while maintaining the performance of the compression system.
Message From The Dean Of The Faculty, Philip Ogunbona
Message From The Dean Of The Faculty, Philip Ogunbona
Professor Philip Ogunbona
The Faculty of Informatics at the University of Wollongong is proud to be co-hosting the 2010 IEEE International Symposium on Technology and Society. It is very fitting that this symposium is being held at the University of Wollongong where a purpose-built faculty has been created to educate graduates who will become leaders and provide technological solutions to the complex problems in the information and communication industry and society at large.
A Fast Algorithm For Color Image Segmentation, L. Dong, P. Ogunbona, Wanqing Li, G. Yu, L. Fan, G. Zheng
A Fast Algorithm For Color Image Segmentation, L. Dong, P. Ogunbona, Wanqing Li, G. Yu, L. Fan, G. Zheng
Professor Philip Ogunbona
Based on K-means and a two-layer pyramid structure, a fast algorithm is proposed for color image segmentation. The algorithm employs two strategies. Firstly, a two-layer structure of a color image is established. Then, an improved K-means with integer based lookup table implementation is applied to each layer. The clustering result on the upper layer (lower resolution) is used to guide the clustering in the lower layer (higher resolution). Experiments have shown that the proposed algorithm is significantly faster than the original K-means algorithm while producing comparable segmentation results.
Compression Tolerant Dct Based Image Hash, C. Kailasanathan, R. Safavi-Naini, P. Ogunbona
Compression Tolerant Dct Based Image Hash, C. Kailasanathan, R. Safavi-Naini, P. Ogunbona
Professor Philip Ogunbona
With the advent of Internet image authentication has become a central part of research in security. Since JPEG has recommended discrete cosine transform as one of the steps in image compression systems, a hash function which utilizes discrete cosine decomposition is desirable. In this paper, we propose a discrete cosine based hash function which distinguishes acceptable level of compression from image processing modifications such as Median filtering, Gaussian noise addition, and FMLR attack. To increase manipulation detection, we optimize the number of AC coefficients needed in smoothing.
Age Estimation Based On Extended Non-Negative Matrix Factorization, Ce Zhan, Wanqing Li, Philip Ogunbona
Age Estimation Based On Extended Non-Negative Matrix Factorization, Ce Zhan, Wanqing Li, Philip Ogunbona
Professor Philip Ogunbona
Previous studies suggested that local appearance-based methods are more efficient than geometric-based and holistic methods for age estimation. This is mainly due to the fact that age information are usually encoded by the local features such as wrinkles and skin texture on the forehead or at the eye corners. However, the variations of theses features caused by other factors such as identity, expression, pose and lighting may be larger than that caused by aging. Thus, one of the key challenges of age estimation lies in constructing a feature space that could successfully recovers age information while ignoring other sources of …
Evaluating The Optimal Probability Distribution For Steganography Under Zero-Error Conditions, Gareth Brisbane, Reihaneh Safavi-Naini, Philip Ogunbona
Evaluating The Optimal Probability Distribution For Steganography Under Zero-Error Conditions, Gareth Brisbane, Reihaneh Safavi-Naini, Philip Ogunbona
Professor Philip Ogunbona
Information hiding can be performed under the guise of a digital image. We consider the following scenario: Alice and Bob share an image and would like to use it as a cover image to communicate a message m. We are interested in answering two questions: What is the maximum amount of information that can be sent for a given level of degradation to an image? and How can this level of efficiency be achieved in practice? We require the recovered message to be the same as the embedded one. Our model begins with Alice compressing a message to obtain a …
Object Detection Using Non-Redundant Local Binary Patterns, Duc Thanh Nguyen, Zhimin Zong, Philip Ogunbona, Wanqing Li
Object Detection Using Non-Redundant Local Binary Patterns, Duc Thanh Nguyen, Zhimin Zong, Philip Ogunbona, Wanqing Li
Professor Philip Ogunbona
Local Binary Pattern (LBP) as a descriptor, has been successfully used in various object recognition tasks because of its discriminative property and computational simplicity. In this paper a variant of the LBP referred to as Non-Redundant Local Binary Pattern (NRLBP) is introduced and its application for object detection is demonstrated. Compared with the original LBP descriptor, the NRLBP has advantage of providing a more compact description of object’s appearance. Furthermore, the NRLBP is more discriminative since it reflects the relative contrast between the background and foreground. The proposed descriptor is employed to encode human’s appearance in a human detection task. …
Signal Analysis Using A Multiresolution Form Of The Singular Value Decomposition, Ramakrishna Kakarala, Philip Ogunbona
Signal Analysis Using A Multiresolution Form Of The Singular Value Decomposition, Ramakrishna Kakarala, Philip Ogunbona
Professor Philip Ogunbona
This paper proposes a multiresolution form of the singular value decomposition (SVD) and shows how it may be used for signal analysis and approximation. It is well-known that the SVD has optimal decorrelation and subrank approximation properties. The multiresolution form of SVD proposed here retains those properties, and moreover, has linear computational complexity. By using the multiresolution SVD, the following important characteristics of a signal may be measured, at each of several levels of resolution: isotropy, sphericity of principal components, self-similarity under scaling, and resolution of mean-squared error into meaningful components. Theoretical calculations are provided for simple statistical models to …
Stereoscopic Panoramic Video Generation Using Centro-Circular Projection Technique, Chaminda Weerasinghe, Wanqing Li, Philip Ogunbona
Stereoscopic Panoramic Video Generation Using Centro-Circular Projection Technique, Chaminda Weerasinghe, Wanqing Li, Philip Ogunbona
Professor Philip Ogunbona
This paper presents a method of stereoscopic panoramic video generation including techniques for panorama projection, stitching and calibration for various depth planes. The methods described can be used on video sequences captured by an arrangement of multiple pairs of cameras or multiple stereoscopic cameras mounted on a regular polygonal shaped camera rig. Algorithms can also be used in combination or separately, for generating both stereoscopic and monoscopic video and still panoramas.
Digital Watermarks For Copyright Protection, Nicholas Paul Sheppard, Reihaneh Safavi-Naini, Philip Ogunbona
Digital Watermarks For Copyright Protection, Nicholas Paul Sheppard, Reihaneh Safavi-Naini, Philip Ogunbona
Professor Philip Ogunbona
It is feared that the ease with which digital media can be copied will lead to a proliferation of copyright infringement. One proposed technical solution is digital watermarking, which embeds a hidden signal into host data that can be used in a variety of protocols that attempt to either prevent or deter copyright infringement. In this paper, we give a brief overview of digital watermarking and discuss some of the issues involved in providing effective digital watermarking systems for deterring copyright infringement.
New Wavelet Based Art Network For Texture Classification, Jiazhao Wang, Golshah Naghdy, Philip O. Ogunbona
New Wavelet Based Art Network For Texture Classification, Jiazhao Wang, Golshah Naghdy, Philip O. Ogunbona
Professor Philip Ogunbona
A new method for texture classification is proposed. It is composed of two processing stages, namely, a low level evolutionary feature extraction based on Gabor wavelets and a high level neural network based pattern recognition. This resembles the process involved in the human visual system. Gabor wavelets are exploited as the feature extractor. A neural network, Fuzzy Adaptive Resonance Theory (Fuzzy ART), acts as the high level decision making and recognition system. Some modifications to the Fuzzy ART make it capable of simulating the post-natal and evolutionary development of the human visual system. The proposed system has been evaluated using …
Secure Compression Using Adaptive Huffman Coding, C. Kailasananathan, Reihaneh Safavi-Naini, Philip Ogunbona
Secure Compression Using Adaptive Huffman Coding, C. Kailasananathan, Reihaneh Safavi-Naini, Philip Ogunbona
Professor Philip Ogunbona
Recent developments in the Internet and Web based technologies require faster communication of multimedia data in a secure form. Standard compression algorithms such arithmetic coding schemes, and propose methods of protecting against these attacks. In the next section we review DHC, and in Section 3 describe DHC encryption scheme and examine possible attacks. In Section 4, we propose an encryption scheme that protects against the attacks and in Section 5 give the results of our experiments. Section 6, concludes the paper. as JPEG and MPEG use an entropy coding stage. By incorporating security in this stage it it possible to …
Shape Vq-Based Adaptive Predictive Lossless Image Coder, Jiazhao Wang, Philip Ogunbona, Golshah Naghdy
Shape Vq-Based Adaptive Predictive Lossless Image Coder, Jiazhao Wang, Philip Ogunbona, Golshah Naghdy
Professor Philip Ogunbona
A new shape adaptive predictive lossless image coder is proposed. Three classes of block shapes are delineated with associated “optimum” predctors. Each image is partitioned into sub-blocks that are classified into one of the three classes using vector quantisation. The encoder then employs the predictor corresponding to the class of the block under consideration. Performance evaluation of the proposed coder in comparison with four other lossless coders includmg lossless JPEG indicates its superiority.
Face Recognition From Single Sample Based On Human Face Perception, Ce Zhan, Wanqing Li, Philip Ogunbona
Face Recognition From Single Sample Based On Human Face Perception, Ce Zhan, Wanqing Li, Philip Ogunbona
Professor Philip Ogunbona
Although research show that human recognition performance for unfamiliar faces is relatively poor, when the sample is always available for analysis and becomes ”familiar”, people are able to recognize a previous unknown face from single sample. In this paper, a method is proposed to deal with the one sample per person face recognition problem based on the process how unfamiliar faces become familiar to people. Particularly, quantized local features which learnt from generic face dataset are used in the proposed method to mimic the prototype effect of human face recognition. Furthermore, a landmark-based scheme is introduced to quantify the distinctiveness …
Hybrid Predictive/Vq Lossless Image Coding, P O. Ogunbona, Jianli Wang, Golshah Naghdy
Hybrid Predictive/Vq Lossless Image Coding, P O. Ogunbona, Jianli Wang, Golshah Naghdy
Professor Philip Ogunbona
A multiplicative autoregressive model is used in a lossless predictive image coding scheme. The use of vector quantisation (VQ) for compression of the model coefficients leads to an improved compression ratio. Both image adaptive and universal codebooks are considered. A comparative analysis of the new coder is presented through simulation results.
2d To Pseudo-3d Conversion Of "Head And Shoulder" Images Using Feature Based Parametric Disparity Maps, Chaminda Weerasinghe, Philip Ogunbona, Wanqing Li
2d To Pseudo-3d Conversion Of "Head And Shoulder" Images Using Feature Based Parametric Disparity Maps, Chaminda Weerasinghe, Philip Ogunbona, Wanqing Li
Professor Philip Ogunbona
This paper presents a method of converting a 2D still photo containing the head & shoulders of a human (e.g. a passport photo) to pseudo-3D, so that the depth can be perceived via stereopsis. This technology has the potential to be included in self-serve photo booths and, also as an added accessory (i.e. software package) for digital still cameras and scanners. The basis of the algorithm is to exploit the ability of the human visual system in combining monoscopic and stereoscopic cues for depth perception. Common facial features are extracted from the 2D photograph, in order to create a parametric …
A 96 X 64 Intelligent Digital Pixel Array With Extended Binary Stochastic Arithmetic, Tarik Hammadou, Magnus Nilson, Amine Bermak, Philip Ogunbona
A 96 X 64 Intelligent Digital Pixel Array With Extended Binary Stochastic Arithmetic, Tarik Hammadou, Magnus Nilson, Amine Bermak, Philip Ogunbona
Professor Philip Ogunbona
A chip architecture that integrates an optical sensor and a pixel level processing element based on binary stochastic arithmetic is proposed. The optical sensor is formed by an array of fully connected pixels, and each pixel contains a sensing element and a Pulse Frequency Modulator (PFM) converting the incident light to bit streams of identical pulses. The processing element is based on binary stochastic arithmetic to perform signal processing operations on the focal plane VLSI circuit. A 96 x 64 CMOS image sensor is fabricated using 0.5pm CMOS technology and achieves 29 x 29pm pixel size at 15% fill factor.