Definition driven image processing for constrained environments

Pervasive computing devices are increasingly deployed to complement and support communication and information systems, propelled by low cost mobile devices that have modest communication, computational and sensing capabilities. Such devices are perfect for personal usage for anytime-anywhere computing, or for speciality tasks that includes unsafe or remote tasks. Fitted with optical and audio sensors, these devices are deployed in a variety of exciting applications including entertainment, communication, high-speed photography, health care, remote telemedicine, law-enforcing activities, security surveillance, disaster rescue management, financial transactions, reconnaissance and biometrics-based authentication. Efficient video processing forms the backbone for many applications. This thesis is concerned with the development of efficient real time video processing techniques to enable and motivate these and new applications. We propose efficient and adaptable techniques in relation to video processing under a constraint, low end and pervasive computing device. Investigations are made towards the following common requirements; capturing high definition data, processing the data for information retrieval and finally fast buffer or data compression. In this thesis, we have primarily investigated and developed video related techniques that require minimal use of memory and are most suitable for implementation on memory constrained devices such as mobile phones. We have developed and implemented procedures that led to significant increase in audio and video data capturing rates, crucial for a multi-modal biometric authentication based system. The developed system maximizes the use of en-board memory and thereby enabling processing higher definition video and audio data.EThOS - Electronic Theses Online ServiceGBUnited Kingdo