Fabrication And Parametric Measurements Of N2 Laser Pumped Dye Laser And Its Application To Energy Transfer Studies In Mixed Dyes

Eventhough a large number of schemes have been proposed and develoned for N9 laser ouined dye lasers the relatively low efficiency compelled the scientists to device new methods to improve the system efficiencs. Energy transfer mechanism has been shown to he a convenien tool for the enhancement of efficiency of dye lasers. Th p resent work covers a detailed study of the performance characteristics of a N2 laser pumped dye laser in the con— ventional mode and also, when pumped by the energy transfer mechanism. For .th.e present investigations a dye laser pumped by a'N2 laser (A4200 kw peak power) was fabricated. The grating at grazing incidence was used as the beam expanding device; A t its best performance the system was giving an output peak power of l5 kW for a 5 X lC"3H/l Rh—€ solution in methanol. T he conversion efficiency was 7.5; The output beam was having 3 divergence of 2 mrad and bandwidth o.9 A. Suitable modifications were suggested for obtaining better conversion efficiency and bandwidth.

Effectiveness Of Feature Detection Operators On The Performance Of Iris Biometric Recognition System

Iris Recognition is a highly efficient biometric identification system with great possibilities for future in the security systems area.Its robustness and unobtrusiveness, as opposed tomost of the currently deployed systems, make it a good candidate to replace most of thesecurity systems around. By making use of the distinctiveness of iris patterns, iris recognition systems obtain a unique mapping for each person. Identification of this person is possible by applying appropriate matching algorithm.In this paper, Daugman’s Rubber Sheet model is employed for irisnormalization and unwrapping, descriptive statistical analysis of different feature detection operators is performed, features extracted is encoded using Haar wavelets and for classification hammingdistance as a matching algorithm is used. The system was tested on the UBIRIS database. The edge detection algorithm, Canny, is found to be the best one to extract most of the iris texture. The success rate of feature detection using canny is 81%, False Accept Rate is 9% and False Reject Rate is 10%.