IMPROVEMENT OF THE FINGERPRINT RECOGNITION PROCESS (original) (raw)

FINGERPRINT RECOGNITION ALGORITHM

Biometrics is an emerging field where technology improves our ability to identify a person. The advantage of biometric identification is that each individual has its own physical characteristics that cannot be changed, lost or stolen. The use of fingerprinting is today one of the most reliable technologies on the market to authenticate an individual. This technology is simple to use and easy to implement. The techniques of fingerprint recognition are numerous and diversified, they are generally based on generic algorithms and tools for filtering images. This article proposes a fingerprint recognition chain based on filtering algorithms. The results are retrieved and validated using Matlab.

SURVEY OF PRIMARY METHODS OF FINGERPRINT FEATURE EXTRACTION

Proving the identity of the individual today is an urgent need in many areas, including social security, financial, criminal and other fields. Biometrics is interested in identifying individuals through personality traits, eye color, fingerprints, height, facial appearance, and signature. Image processing technology supports most of the techniques used in biometrics, by improving images and matching images, to identify the individual identity. Fingerprint recognition is some of the most well-known biometrics, and it the best the used biometric result for confirmation on computer systems. Technic fingerprinting has a great popularity for simplicity of acquisition, the use and approval when compared to other systems. Fingerprint Recognition System consists of four steps: firstly, Image acquisition (image fingerprint) through sensors .Secondly, processing the image so that it obscures the noise that exists, clarifying the hills. Thirdly, Extracting features of injury fingerprints. Fourth, compare the acquired features with features of fingerprint fingerprints in databases. The aim of this paper is to present the latest research in the applications of fingerprint recognition systems.

A survey on Fingerprint Biometric System Stages

This article is an overview of the basic architecture of the fingerprint system. We described the methodology of the Automated Fingerprint Identification System and the approaches and techniques used to obtain, analyze, match fingerprint, we also detailed the some techniques for feature extraction and matching stages; The paper divided into three parts; the first part is an introduction to the Automated Fingerprint Identification System and also provides a summarized description of fingerprint image preprocessing and a survey on some papers highlighted on fingerprint preprocessing techniques. The second part gives a detailed description of the fingerprint feature extraction technique regarding fingerprint identification and verification; the last part gives a description of the matching methods and approaches; we also provided a literature review of some of the methodologies and techniques used in the various stages of the Automated Fingerprint Identification system.

A Study on Fingerprint (biometrics) Recognition

Till now many algorithms are published for fingerprint recognition and these algorithms has different accuracy rate. This paper consists of information of about fingerprint (biometrics) recognition. The novel algorithm is considered for thinning process. Whole process of recognition is explained from image capturing to verification. The image captured is first converted to gray scale then image enrichment is done then thinning process take over charge which is main process then last process which is also equally important as thinning process is feature extraction which extracts ridge ending, bifurcation, and dot. The accuracy depends on the result of the three main process namely pre-processing, thinning process and feature extraction. Keywords: Arch, loop, whorl, Preprocessing, Thinning Process, Feature Extraction, Ridge. I. INTRODUCTION

Overview of Fingerprint Recognition System

— This article is an overview of a current research based on fingerprint recognition system. In this paper we highlighted on the previous studies of fingerprint recognition system. This paper is a brief review in the conceptual and structure of fingerprint recognition. The basic fingerprint recognition system consists of four stages: firstly, the sensor which is used for enrolment & recognition to capture the biometric data. Secondly, the pre-processing stage which is used to remove unwanted data and increase the clarity of ridge structure by using enhancement technique. Thirdly, feature extraction stage which take the input from the output of the pre-processing stage to extract the fingerprint features. Fourthly, the matching stage is to compare the acquired feature with the template in the database. Finally, the database which stores the features for the matching stags. The aim of this paper is to review various recently work on fingerprint recognition system and explain fingerprint recognition stages step by step and give summaries of fingerprint databases with characteristics.

An Efficient Approach for Robust Fingerprint Recognition System

In today’s society, the use of electronic commerce, transaction of monetary assets and daily use of email is rapidly increasing. Along with the increased ease of purchasing and selling, there is also an increase in fraud mostly from false identification. Solutions to this problem have been in the field of biometrics, using the person’s body as a form of identification. In particular, the uniqueness of fingerprints has made them very popular among law enforcement, banking establishments and commerce. Fingerprint identification using manual procedures has become a very common approach, but it has number of limitations like very low rate of positive identification, time consumption, mutilation of paper slips used for fingerprinting, etc.., rendering them ineffective. This has resulted in the dire need of speeding up the procedure and increasing its reliability by the use of computerized process. This paper addressing different procedures involved in acquisition of the fingerprint, operations of pre-processing to make the fingerprint compatible for feature extraction, feature extraction and finally authentication are discussed along with their associated difficulties.

IJERT-Fingerprint Recognition and its Advanced Features

International Journal of Engineering Research & Technology (IJERT), 2020

https://www.ijert.org/fingerprint-recognition-and-its-advanced-features https://www.ijert.org/research/fingerprint-recognition-and-its-advanced-features-IJERTV9IS040393.pdf Fingerprint recognition is one of the most popular and successful methods used for person identification, which takes advantage of the fact that the fingerprint has some unique characteristics called minutiae; which are points where a curve track finishes, intersect with other track or branches off. Biometric identification systems using fingerprints patterns are called AFIS (Automatic Fingerprint Identification System). Fingerprint Recognition is one of the research hot spots in Biometric. It refers to the automated method of verifying a match between two human fingerprints. It is essentially a challenging pattern recognition problem where two competing error rates: the False Accept Rate (FAR) and the False Reject Rate (FRR) need to be minimized. Advancement of computing capabilities led to the development of Automated Fingerprint Authentication Systems (AFIS) and this led to extensive research especially in the last two decades. In this paper, we attempt to give a comprehensive scoping of the fingerprint recognition problem and address its major design and implementation issues as well as give an insight into its future prospects.

Fingerprint-Based Verification System

2010

The design and implementation of a fingerprint verification system is presented. The system is capable of segmentation, fingerprint enhancement using Gabor filters, thinning, minutiae extraction, classification and matching. The system has been tested on four sets of fingerprint images used at Fingerprint Verification Competition 2002 (FVC2002). All steps except enhancement were found to be effective. Especially the sensitivity to fingerprint quality should be taken care of in the future. Processing time of 3 seconds on average meets the response time requirements of a simple fingerprint verification system. Keywords-Fingerprints, fingerprint verification, FVC2002, fingerprint reader.

Performance Evaluation of the Automatic Fingerprint Recognition System

The biometric characteristics that are used in the authentication system are unique for each person. The major advantage of the biometrics is that you have always with your way to authenticate yourself. Furthermore biometrics make it possible to know who is authenticated and where. Fingerprint is taken as proffered technique for the biometric authentication because of the public acceptability, ease of use, economy of scale, easy installation and availability. There are two approaches to fingerprint recognition minutia base and image based but in this paper we limit to the minutia based recognition. In this paper we evaluate the minutia as per three stage approach and given the performance evaluation especially for the false minutia and the fingerprint classifiers. The estimation of the previously used scheme and the new scheme is analysed and the results were appreciating.

Review on Fingerprint Recognition

—Biometric system works on behavioral and physiological biometric parameters to spot a person. Every fingerprint contains distinctive options and its recognizing system primarily works on native ridge feature local ridge endings, minutiae, core point, delta, etc. However, fingerprint pictures have poor quality thanks to variations in skin and impression conditions. In personal identification, fingerprint recognition is taken into account the foremost outstanding and reliable technique for matching with keep fingerprints within the information. Minutiae extraction is additional essential step in fingerprint matching. This paper provides plan regarding numerous feature extraction and matching algorithms for fingerprint recognition systems and to seek out that technique is additional reliable and secure. Keywords— fingerprint images, minutiae extraction, ridge endings, ridge bifurcation, fingerprint recognition.