Master of Engineering in Electronics and Telecommunications

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Browsing Master of Engineering in Electronics and Telecommunications by Subject "Electronic and Telecommunication Engineering-Thesis"

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    item: Thesis-Abstract
    Content-based image retrieval using large centre regions
    Senaratne, RS; Pasqual, AA
    Among all the visual features used for content-based image retrieval, colour is perhaps the most dominant and distinguishing one in many applications. Therefore in this research project, the concentration was focused on the colour property of images. In this work, a new histogram refinement technique, Large Centre Regions (LCR) Refinement, and a new region representation technique, LCR Sets, based on colour regions are presented. These methods extract a selected number of largest regions around the centre of the image and match other images emphasizing this property. Two assumptions are made. First is, that it can be assumed that the significant objects oritems of an image are often located at the centre. These objects can often be characterized by their colour. Hence an image retrieval technique which extracts the colours of large centre regions of an image would improve the retrieval performance for images with significant objects at the centre. The second is, that the techniques were tested on an image data base predominantly consisting of red images, but they perform similarly for other colours as well. The presented histogram refinement descriptor, Large-Centre-Regions Vector, effectively represents large centre regions of an image. In addition to this, LCR Sets represent basic information about the shape of a region. In the prototype, firstly, all the regions in an image were extracted depending on the similarity of the colour of the pixels. A centre zone was defined on the image and a selected number of largest regions which overlap with this centre zone at least by 50% of the region area were selected as the Large-Centre-Regions for histogram refinement basis. In addition to large centre regions, LCR Sets represent the areas of a selected umber of largest regions lying outside the centre zone and the width to height ratio of the minimum bounding rectangle of each region. Since the largest regions at the centre are given the emphasis for matching, effect of the background can be minimized as well because most part of the background often lies outside the centre zone. Extra distinguishing capability among different images can be achieved with LCR Sets.Experimental results of LCR Refinement show much improved retrieval performance, especially for images with significant regions at the centre. Results show 20% average improvement in ranks with LCR Refinement compared to Histogram. By combining LCR Sets with either Histogram or LCR Refinement, this can be further improved upto 26% or 22%, respectively.
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    item: Thesis-Abstract
    Smart base station antenna
    Punchihewa, SAS; Dayawansa, IJ
    Telecommunications incur a strong impact on the society. Out of its many sectors, mobile communications experienced an unprecedented growth around the globe in recent times .Service providers will have to satisfy this increased customer need using a spectrum, which does not grow proportionately. Several multiple access systems such as frequency division multiple access, time division multiple access and code division multiple access are used at present to increase the efficiency of spectrum utilization. The smart antenna, consisting of an array of elements, monitors its signal environment and forms a beam towards the wanted signal. Thus, on top of the existing access methods it provides an additional multiple access method namely space division multiple access in which several users access portions of space simultaneously. There exist different methods or algorithms for formation of the beam towards the desired signal. Some of them form a beam and rotate while monitoring the satisfaction of certain conditions, which indicate the correct formation of the beam. Some others find the directions of arrival of signals (DOA) and then form the beam towards the desired direction of which the resolution is higher. In spite of high-resolution capability, these algorithms demand knowledge of the propagation characteristics of the mobile channel. This necessitates modeling of the channel after theoretical or empirical considerations. This dissertation presents the work carried out to determine the DOA of a desired signal which is to be used in an adaptive antenna in a variety of propagation channels. The suitability of MUSIC (Multiple Signal Classification) algorithm was investigated. It was necessary to find the ability of the algorithm to estimate the DOA of impinging signals. However, the channel modeling was also a necessity. To determine the accuracy of the estimation, the error between the actual and estimated DOA was determined and analyzed. MATLAB was used for simulations because of its capabilities to handle large amount of matrix related computational activities efficiently. An artificial channel with free space conditions was initially used to test the method of estimating the DOA, and to check the suitability of error analysis as a method of determining the accuracy. In this artificial channel, estimation of several DOA was performed for different conditions of environment monitoring and different antenna array geometry. Different number of signals was used with different angles of arrival. Hence, the dependence of errors on the above different conditions was determined and there by the suitability of the error analysis to determine the accuracy was examined. by European Union were used and the performance of the MUSIC algorithm in different channel conditions was analyzed. Using the measured signal value data in the Colombo Fort area, the channel was mathematically modeled and MUSIC algorithm was tested for Colombo Fort. MUSIC algorithm was found to be suitable for use in adaptive cellular base station antenna.
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    item: Thesis-Abstract
    Use of ground penetrating radar for landmine classification based on artificial neural network
    Fernando, PSL; Munindradasa, DAI
    This research is mainly aimed at developing a technique based on neural networks to classifymetal and plastic objects buried within a range of soil conditions. In addition, the validity of this technique is also presented. The explosives in land mines are generally cased in metal or plastic containers. Identification of buried metal and plastic objects using a neural network and a sensing teclmique based on an electromagnetic method are discussed in this thesis. Neural network simulation results for plastics and metal objects in the range of soil condition are also reported. Finding the appropriate frequency window (FvV) for the Ground Penetrating Radar(CPR) operation and the development of a theoretical mathematical model is also presmted. Using this model, the appropriate FW for CPR operation is derived. Furthermore the estimation of important system parameters of CPR, modulation and detection techniques, modelling of CPR, and clutter reduction techniques are also discussed in the context of this thesis.
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    item: Thesis-Abstract
    Wavelet packet based antenna radiation pattern analyser
    Wimalshanthi, W; Jayasinghe, JAKS
    Analysis of antenna radiation patterns, especially in respect of antennas with complex shapes and sizes, require the adoption of numerical methods of obtaining solutions to electro-magnetic equations. Method of Moments (MOM) being one of such proven methods, still poses the problem of manipulation of large matrices. Objective of this exercise is to investigate the possibility of using wavelet transform techniques in obtaining fast solutions for the matrix equations resulting from MOM method. Specific attention has been given to Discreet Wavelet Transform (DWT) and Discreet Wavelet Packet (DWP) transform methods in order to spar sify the large impedance matrices generated by MOM method. Wavelet transform being a recently developed technique, the mathematical background and related theoretical aspects have been illustrated prior to analysing several examples of thin wire centre fed antennas. Examples have been selected to demonstrate effective adaptation of Discrete Wavelet Transform and Discrete Wavelet Packet Transform techniques in obtaining solutions for the matrix equations in the analysis of thin wire antennas. Comparisons have been made with the conventional method of solving these matrix equations illustrating the improvement in the computation times as a result of sparsification of matrices using Wavelet transform methods with the extensive assistance of Mat Lab Wavelet Tool Box. Having indicated the advantages of wavelet transform techniques over the conventional methods of solving large matrix equations, several suggestions have been made towards optimising the results obtained to be taken up as further research work.