Digital image processing is the use of computer processes to perform image processing on digital images. It allows a much extensive range of processes to be applied to the input data and can avoid problems such as the build-up of noise and signal alteration during processing. In imaging science, image processing is processing of images using accurate operations by using any form of signal allowance for which the input is an image, a series of images or a video, such as a picture or video frame; the output of image processing may be either an image or a set of features. In this paper the problem of ‘ngerprint veri’cation via the Internet is considered.[1] Speci’cally, the method that is used for the above purpose is based on a outdated ‘nger scanning technique, connecting the analysis of small unique marks of the ‘nger image known as minutiae. Minutiae points are the ridge finales or divisions branches of the ‘nger image. The relative position of these minutiae is used for comparison, and according to empirical studies, two characters will not have eight or more common details.[2]
KEY WORDS
Fingerprinting, Image matching, feature extraction, minutia details.
1. INTRODUCTION
In computer science and electronic engineering image treatment, image processing is any form of processing of signals for which the input is an image, such as pictures or frames of video the output of image processing can be each an image or a set of individual or parameters related to the image. Image processing systems have been developed tremendously during past five decades. Sometimes a difference is made by defining image processing as a correction in which both input and output of a process are image. Biometrics, which refers to identifying an individual based on his or her functional or behavioural characteristics, has the capability to consistently distinguish between an authorized person and an pretender.[3] Since biometric characteristics are distinctive, cannot be overlooked or lost, and the person to be valid needs to be physically present at the point of identification, biometrics is naturally more reliable and more capable than traditional knowledge-based and token-based techniques. Biometrics also has a number of disadvantages. For example, if a password or an ID card is compromised, it can be easily replaced. However, once a biometrics is cooperated, it is not possible to replace it. Similarly, users can have a different password for each version, thus if the password for one account is compromised, the other accounts are still safe.[4]
Skin on human fingertips holds points and dells which together forms characteristic patterns. These patterns are fully recognised under condition and are permanent throughout total lifetime. Prints of those designs are called fingerprints. Wounds like cuts, burns and bumps can provisionally damage worth of fingerprints but when completely healed, patterns will be restored.[5] Automatic fingerprint recognition has become a usually used technology in both medical and biometrics applications. Despite a part of a thousand years during which finger prints have been used as character’s proof of identity and years of research on automated systems, reliable fully mindless fingerprint recognition is still an unexplained motivating research problem. Moreover, most of research thus far, accepts that two finger print patterns being matched are about of the same size and cover large areas of fingertip. However, this statement is no longer valid. The reduction of finger print sensors has led to small sensing areas and can only capture incomplete fingerprints. Unfinished fingerprints are also common in forensic applications.
2. FINGERPRINT IMAGE PROCESSING
A fingerprint recognition system constitutes of fingerprint device, Features extractor and Features matching. For fingerprint gaining, optical or semi-conduct devices are extensively used. They have great efficiency and acceptable accuracy except for some cases that user’s finger is too unclean or dry.[6]
Fingerprint Features
There are mostly three key fingerprint features
‘ Global Ridge Pattern
‘ Local Ridge Detail
‘ Intra Ridge Detail
Global Ridge Detail
There are two forms of ridge flows: the self-styled-matching ridge flows and high-bend ridge flows which are located round the core point and/or delta points.