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dc.contributor.authorBody, Nick
dc.date.accessioned2011-02-24T01:01:53Z
dc.date.availableNO_RESTRICTIONen_US
dc.date.available2011-02-24T01:01:53Z
dc.date.issued2000
dc.identifier.urihttp://hdl.handle.net/10179/2151
dc.descriptionContent removed due to copyright restriction: Body, N. B. and Bailey, D. G., "Efficient Representation and Decoding of Static Huffman Code Tables in a Very Low Bit Rate Environment, " Proceedings of IEEE International Conference on Image Processing (ICIP-98), Chicago, USA, pp.90- 94, vol. 3, 4-7 October, 1998. Body, N. B.; Page, W. H.; Khan, J. Y.; Hodgson, R. M., and Collins, F. A. H., "Efficient Wavelet Image Coding on a Digital Signal Processor Based Digital Camera, " Proceedings of International Conference on Signal Processing Applications & Technology (ICSPAT -98), Toronto, Canada, pp.782-786, 13-16 September, 1998. Body, N. B.; Page, W. H.; Khan, J. Y., and Hodgson, R. M., "Efficient Digital Signal Processor Implementation of a Wavelet Transform Based Image Compression Algorithm, " Proceedings of Digital Image and Vision Computing: Techniques and Applications (DICT AllVCNZ-97), Albany Campus, Massey University, Auckland, New Zealand, pp. 71-76, 10-12 December, 1997.en_US
dc.description.abstractThis thesis describes the development of image processing algorithms to achieve industrial remote activity monitoring. The design of such algorithms is constrained by the requirement that they must be implemented in real-time on a cost effective digital signal processor (DSP). A review of the literature revealed that two viable alternatives were available. These are JPEG, a well established lossy block-based image compression algorithm and methods using wavelets. A suitable family of wavelets was identified as the biorthogonal-7.9, the coefficients indicating the number of taps in the quadrature mirror filters at the heart of the transform. Data compression is then achieved through the construction of zerotrees followed by sequential baseline coding. The two candidate algorithms were then systematically compared for recovered image quality and implementation cost at high compression ratios in the range of 16:1 to 64:1. On this basis the wavelet approach was selected and its implementation on a DSP studied. The architectural features of the Motorola 56303 DSP are presented and analysed. It is shown that the various components required for the wavelet based algorithm can be efficiently mapped onto the DSP architecture. Motion detection and image watermarking algorithms were designed and co-operatively implemented with the compression algorithm. A new method of watermarking highly compressed images was developed and this algorithm has been named the Image Authentication Watermark. A new way of representing optimal Huffman code tables has been developed to enable Huffman entropy coding to perform competitively with the more complex arithmetic coding. A product of this research is a smart digital camera that has been integrated into an automated video surveillance system now in industrial production.en_US
dc.language.isoenen_US
dc.publisherMassey Universityen_US
dc.rightsThe Authoren_US
dc.subjectDigital signal processingen_US
dc.subjectImage processingen_US
dc.subjectData processingen_US
dc.subjectDigital techniquesen_US
dc.subject.otherFields of Research::290000 Engineering and Technology::291700 Communications Technologies::291703 Digital systemsen_US
dc.titleImage processing and DSP technology applied to remote activity monitoring : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Technology at Massey Universityen_US
dc.typeThesisen_US
thesis.degree.disciplineTechnologyen_US
thesis.degree.grantorMassey Universityen_US
thesis.degree.levelDoctoralen_US
thesis.degree.levelDoctoralen
thesis.degree.nameDoctor of Philosophy (Ph.D.)en_US


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