A Dual System Capture Biometric Fingerprint Scanner

2013

The diffusion of mobile cameras and webcams is rapidly growing. Unfortunately, images produced by these kinds of sensors during the acquisition of human fingertips are very different from the images obtained by dedicated fingerprint sensors, especially as quality is concerned. One critical issue regarding the protection of confidential information or valuable items is to determine the identity of a person. Biometrics is supposed to offer this security in a user-friendly and secure way. One problem however is that there are ways to compromise systems based on biometric verification. Some of these biometrical features have known vulnerabilities. Persons with similar facial characteristics, e.g. identical twins, can fool face recognition system. It is also stated that identical twins have similar fingerprints due to the fact that they have fingerprints that belong in the same class. Recognition of a finger prints it is necessary to get better image quality of finger print to get better image. So designed a low cost finger print sensor & adjusted its various parameters to improve finger print image quality. We used optical finger print reader using a low cost webcam for capturing image. Image saved in computer. Edge was determined from image using visual C++ program of different person. The result of this experiment was not found very well because it is a big experiment & its program is very difficult. There are many programs we had done for finding better image. We had used image loading program, capturing program, image saving program, zoom in program etc.

International Journal for Scientific Research and Development, 2015

Every human has distinct physiological as well as behavioral characteristics and to recognize each individual we need a biometric system that provides a wide variety of reliable personal recognition schemes either in form of confirmation or determination. The purpose of such schemes is to make sure that the services are only accessed by a genuine user, and no one else use of it. This includes fingerprint, voice, face, gait, iris, signature, hand geometry etc. Mainly the biometric system consists of four main modules i.e. sensor module, feature extraction module, matching module and decision module. In a biometric system, sensor module is the first module so it is very essential to have accurate acquisition of data over there. In this paper various type of fingerprint sensors are discussed in detail. There are some parameters like pixel density, resolution, SN ratio, motion blur, gray scale etc. of these sensors which are also included. Sensors also encounter some challenges like dur...

2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011

and Computer Engineering To counter certain security threats in biometric authentication systems, particularly in portable devices (e.g., phones and laptops), we have developed a technology for automated authentication of fingerprint scanners of exactly the same type, manufacturer, and model. The technology uses unique, persistent, and unalterable characteristics of the fingerprint scanners to detect attacks on the scanners, such as detecting an image containing the fingerprint pattern of the legitimate user and acquired with the authentic fingerprint scanner replaced by another image that still contains the fingerprint pattern of the legitimate user but has been acquired with another, unauthentic fingerprint scanner. The technology uses the conventional authentication steps of enrolment and verification, each of which can be implemented in a portable device, a desktop, or a remote server. The technology is extremely accurate, computationally efficient, robust in a wide range of conditions, does not require any hardware modifications, and can be added (as a software add-on) to systems already manufactured and placed into service. We have also implemented the technology in a demonstration prototype for both area and swipe scanners.

Open Computer Science, 2011

The article is aimed at fingerprint recognition or verification, which is used mainly in access control systems. The proposed method of fingerprint verification uses image registration (reconciliation) by applying the Fourier-Mellin transform and consequently compares images by the Fourier transform using modified phase correlation.

TELKOMNIKA Telecommunication Computing Electronics and Control, 2018

The idea of security is as old as humanity itself. Between oldest methods of security were included simple mechanical locks whose authentication element was the key. At first, a universal-simple type, later unique for each lock. A long time had mechanical locks been the sole option for protection against unauthorized access. The boom of biometrics has come in the 20th century, and especially in recent years, biometrics is much expanded in the various areas of our life. Opposite of traditional security methods such as passwords, access cards, and hardware keys, it offers many benefits. The main benefits are the uniqueness and the impossibility of their loss. The main benefits are the uniqueness and the impossibility of their loss. Therefore we focussed in this paper on the the design of low cost biometric fingerprint system and subsequent implementation of this system in praxtise. Our main goal was to create a system that is capable of recognizing fingerprints from a user and then processing them. The main part of this system is the microcontroller Arduino Yun with an external interface to the scan of the fingerprint with a name Adafruit R305 (special reader). This microcontroller communicates with the external database, which ensures the exchange of data between Arduino Yun and user application. This application was created for (currently) most widespread mobile operating system-Android.

International Journal of Biosensors & Bioelectronics

Biometrics provides an alternative paradigm for the personal authentication: our biological characteristics are unique and can be used to distinguish us from the other persons. Biometrics are automated methods of identifying a person or verifying the identity of a person based on a physiological or behavioral characteristic. Examples of physiological characteristics include hand or finger images, facial characteristics, and iris recognition. Behavioral characteristics are traits that are learned or acquired. Dynamic signature verification, speaker verification, and keystroke dynamics are examples of behavioral characteristics. In this paper a general overview of biometric systems based on the principal biometric technologies available and a description of a fingerprint recognition sensor performances are proposed. To test the biometric sensor performances two indexes are used, FAR (false accept rate) and FRR (false reject rate).

Pattern Recognition Letters, 2004

A few works have been presented so far on information fusion for fingerprint verification. None, however, have explicitly investigated the use of multi-sensor fusion, in other words, the integration of the information provided by multiple devices to capture fingerprint images. In this paper, a multi-sensor fingerprint verification system based on the fusion of optical and capacitive sensors is presented. Reported results show that such a multi-sensor system can perform better than traditional fingerprint matchers based on a single sensor.

Fingerprints are one of the most mature bio-metric technologies and are considered legitimate proofs of evidence in courts of law all over the world. In recent times, more and more civilian and commercial applications are either using or actively considering using fingerprint-based identification because of the availability of inexpensive and compact solid state scanners as well as its superior and proven matching performance over other bio-metric technologies.

Internet of Things and Artificial Intelligence Journal

study aims to create a Fingerprint Sensor Implementation System for a Fingerprint Reader Prototype Using a Microcontroller. Implementing the Fingerprint Sensor for the Fingerprint Reader Prototype is run by an application connected by a USB cable. The Fingerprint Sensor Implementation System for the Fingerprint Reader Prototype is made for fast and more accurate attendance and cannot be manipulated. The Fingerprint Sensor Implementation System for the Fingerprint Reader Prototype is the problem. Namely, the attendance problem, which is still manual using books; after that, the design and manufacture of the Fingerprint Reader prototype using a Microcontroller or applications through NetBeans. Then implementation and testing. Then at the trial stage, the Arduino application was carried out. The result of this study is the Fingerprint Sensor Implementation System for the Prototype Fingerprint Reader Using a Microcontroller and development in the Internet of Things.