Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 10 of 10
Full-Text Articles in Physical Sciences and Mathematics
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.
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.
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 …
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 …
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.