Investigations on the Radiation Characteristics of Broadband Strip Loaded Slotted Microstrip Antennas

With the recent progress and rapid increase in mobile terminals, the design of antennas for small mobile terminals is acquiring great importance. In view of this situation, several design concepts are already been addressed by the scientists and engineers. Compactness and efficiency are the major criteria for mobile terminal antennas. The challenging task of the microwave scientists and engineers is to device compact printed radiating systems having broadband behavior, together with good efficiency. Printed antenna technology has received popularity among antenna scientists after the introduction of microstrip antenna in 1970s. The successors in this kind such as printed monopoles and planar inverted F are also equally important. Scientists and Engineers are trying to explore this technology as a viable coast effective solution for forthcoming microwave revolution. The transmission line perspectives of antennas are very interesting. The concept behind any electromagnetic radiator is simple. Any electromagnetic system with a discontinuity is radiating electromagnetic energy. The size, shape and the orientation of the discontinuities controls the radiation characteristics of the system such as radiation pattern, gain, polarization etc. It can be either resonant or non resonant structure. Microstrip antennas are suitable for wireless applications due to their low cost, high gain and ease of fabrication. But the major disadvantage of micro strip antennas is their inherent narrow bandwidth. A lot of techniques are introduced by the researchers all over the world to enhance the bandwidth of micro strip patch antennas. The thesis addresses an attempt to enhance the bandwidth of micro strip patch antennas by incorporating impedance matching strip as a part of the micro strip patch antenna. The first part of the thesis deals with the broadband operation of the tilted square slot and polygonal slot loaded square micro strip patch antennas. The resonant mechanisms are clearly mentioned using the simulation and experimental studies. The bandwidth of the polygonal slotted broadband patch antenna is again enhanced by implementing an Lstrip feed mechanism. In the second major part of the thesis, a novel gain enhancement technique for single band and broadband square micro strip patch antennas is achieved by implementing offset stacked configurations.

Development of a Biometric Personal Authentication System Based on Fingerprint and Speech

Biometrics deals with the physiological and behavioral characteristics of an individual to establish identity. Fingerprint based authentication is the most advanced biometric authentication technology. The minutiae based fingerprint identification method offer reasonable identification rate. The feature minutiae map consists of about 70-100 minutia points and matching accuracy is dropping down while the size of database is growing up. Hence it is inevitable to make the size of the fingerprint feature code to be as smaller as possible so that identification may be much easier. In this research, a novel global singularity based fingerprint representation is proposed. Fingerprint baseline, which is the line between distal and intermediate phalangeal joint line in the fingerprint, is taken as the reference line. A polygon is formed with the singularities and the fingerprint baseline. The feature vectors are the polygonal angle, sides, area, type and the ridge counts in between the singularities. 100% recognition rate is achieved in this method. The method is compared with the conventional minutiae based recognition method in terms of computation time, receiver operator characteristics (ROC) and the feature vector length. Speech is a behavioural biometric modality and can be used for identification of a speaker. In this work, MFCC of text dependant speeches are computed and clustered using k-means algorithm. A backpropagation based Artificial Neural Network is trained to identify the clustered speech code. The performance of the neural network classifier is compared with the VQ based Euclidean minimum classifier. Biometric systems that use a single modality are usually affected by problems like noisy sensor data, non-universality and/or lack of distinctiveness of the biometric trait, unacceptable error rates, and spoof attacks. Multifinger feature level fusion based fingerprint recognition is developed and the performances are measured in terms of the ROC curve. Score level fusion of fingerprint and speech based recognition system is done and 100% accuracy is achieved for a considerable range of matching threshold

Multifinger Feature Level Fusion Based Fingerprint Identification

Fingerprint based authentication systems are one of the cost-effective biometric authentication techniques employed for personal identification. As the data base population increases, fast identification/recognition algorithms are required with high accuracy. Accuracy can be increased using multimodal evidences collected by multiple biometric traits. In this work, consecutive fingerprint images are taken, global singularities are located using directional field strength and their local orientation vector is formulated with respect to the base line of the finger. Feature level fusion is carried out and a 32 element feature template is obtained. A matching score is formulated for the identification and 100% accuracy was obtained for a database of 300 persons. The polygonal feature vector helps to reduce the size of the feature database from the present 70-100 minutiae features to just 32 features and also a lower matching threshold can be fixed compared to single finger based identification