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    Automation of pollen analysis using a computer microscope : a thesis presented in partial fulfilment of the requirements for the degree of Master of Engineering in Computer Systems Engineering at Massey University
    (Massey University, 2004) Holdaway, Craig Alexander
    The classification and counting of pollen is an important tool in the understanding of processes in agriculture, forestry, medicine and ecology. Current pollen analysis methods are manual, require expert operators, and are time consuming. Significant research has been carried out into the automation of pollen analysis, however that work has mostly been limited to the classification of pollen. This thesis considers the problem of automating the classification and counting of pollen from the image capture stage. Current pollen analysis methods use expensive and bulky conventional optical microscopes. Using a solid-state image sensor instead of the human eye removes many of the constraints on the design of an optical microscope. Initially the goal was to develop a single lens microscope for imaging pollen. In-depth investigation and experimentation has shown that this is not possible. Instead a computer microscope has been developed which uses only a standard microscope objective and an image sensor to image pollen. The prototype computer microscope produces images of comparable quality to an expensive compound microscope at a tenth of the cost. A segmentation system has been developed for transforming images of a pollen slide, which contain both pollen and detritus, into images of individual pollen suitable for classification. The segmentation system uses adaptive thresholds and edge detection to isolate the pollen in the images. The automated pollen analysis system illustrated in this thesis has been used to capture and analyse four pollen taxa with a 96% success rate in identification. Since the image capture and segmentation stages described here do not affect the classification stage it is anticipated that the system is capable of classifying 16 pollen taxa, as demonstrated in earlier research.
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    Gesture and voice control of internet of things : a thesis presented in partial fulfilment of the requirements for the degree of Master of Engineering in Electronics and Computer Engineering at Massey University, Auckland, New Zealand
    (Massey University, 2015) Han, Xiao
    Nowadays, people's life has been remarkably changed with various intelligent devices which can provide more and more convenient communication with people and with each other. Gesture and voice control are becoming more and more important and widely used. People feel the control system humanized and individualised using biological control. In this thesis, an approach of combined voice and gesture control of Internet of Things is proposed. A prototype is built to show the accuracy and practicality of the system. A Cortex-A8 processor (S5PV210) is used and the embedded Linux version 3.0.8 has been cross-compiled. Qt 4.8.5 has been ported as a UI (User Interface ) framework and OpenCV 2.4.5 employed as vision processing library. Two ZigBee modules are used to provide wireless communication for device control. The system is divided into control station and appliance station. The control station includes development board, USB camera, voice recognition module, LCD screen and ZigBee module. This station is responsible for receiving input signal (from camera or microphone), analyzing the signal and sending control signal to appliance station. The appliance station consists of relay, ZigBee module and appliances. The ZigBee module in the appliance station is to receive control signal and send digital signal to connected relay. The appliance station is a modular unit that can be expanded for multiple appliances. The system can detect and keep tracking user's hand. After recognizing user's gesture, it can control appliances based on certain gestures. Voice control is included as an additional control approach and voice commands can be adjusted for different devices.