标题：Performance Analysis and Designing of Fingerprints Enhancement Technique Based on Segmentation, oF Estimation and Ridge Frequency, Gabor Filters with Wavelet Transform
期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2014
卷号：5
期号：5
页码：6644-6651
出版社：TechScience Publications
摘要：The objective of image enhancement technique is to improve the overall performance by optimally arranging input images for afterward processing stages. A fingerprint is the pattern of ridges and valleys on the surface of a fingertip. Each person has unique fingerprints. The uniqueness of a fingerprint is exclusively determined by the local ridge characteristics and their relationships. 150 different local ridge distinctiveness like islands, short ridges, enclosure, etc. have been acknowledged. These local ridge distinctiveness are not evenly distributed. Most of them heavily depends on the impression conditions, quality of fingerprints and are not often observed in fingerprints. The two most prominent local ridge characteristics, called minutiae, are ridge ending and ridge bifurcation. A ridge ending can be defined as the point where a ridge ends sharply. A ridge bifurcation is defined as the point where a ridge forks or diverges into branch ridges. A good quality fingerprint characteristically contains approximately 40–100 minutiae. Therefore, how to appropriately extract minutiae from fingerprint images becomes an important step in fingerprint identification. Most systems extract minutiae from fingerprints and the presence of noise can interfere with the extraction of minutiae. As a result, true minutiae may possibly be missed, and false minutiae possibly will be detected and both of these have a negative effect. In order to avoid these two types of errors, image enhancement plans at improving the clarity of the ridge and valley structures. To achieve good minutiae, initially, extraction is done in fingerprints with varying quality, then preprocessing in form of image enhancement. Many methods have been joined to build a minutia extractor and a minutia matcher. The goal of this dissertation is to design a fast fingerprint enhancement algorithm, which can adaptively improve the clarity of ridge and valley structures of input fingerprint images based on the estimated local ridge orientation and frequency, is be implemented in this dissertation work. Performance of the new developed system is then evaluated using visual analysis and goodness index value of enhanced image.
