Detailed Design Specification Template
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- Words: 942
- Pages: 8
Date of Submission : <22nd September 2009>
Submitted by: Group No: < >
1. < Akanksha Tyagi >
<ECE/08/101 >
2. < Anuj Jain >
<ECE/08/160>
3. < Preeti Rana >
<ECE/08/133>
4. < Rahul Jain >
<ECE/08/138>
5. < Rahul Mehra >
<ECE/08/139>
6. < Yatish Tagra >
<ECE/08/157>
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Faculty Comments
Name of Faculty
:
Signature of Faculty
:
Date of Checking
:
Status
:
Approved
Rejected
Date to submit new synopsis (applicable only if status is rejected) : If the synopsis is rejected faculty will mention the reason below and group is required to submit the new synopsis by the date mentioned above. Comments
:__________________________________________________
_______________________________________________________________________ _______________________________________________________________________
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TABLE OF CONTENTS 1 OBJECTIVE AND SCOPE OF PROJECT.........................................................................................1 2 PROCESS DESCRIPTION...................................................................................................................2 3 RESOURCES AND LIMITATIONS....................................................................................................3 4 CONCLUSION.......................................................................................................................................4
1 Objective and Scope of Project The overall objective of the project is to develop a finger print system based on directional filter bank technique which works on minutiae. A point in the fingerprint image is designated as a minutia if it belongs to an ending, beginning or bifurcation of a ridge. The extraction of minutiae relies heavily on the quality of the input images. S imple smoothing and sharpening Contrast stretching Dry and wet area detection Scope In order to aid forensics in criminal identification, authentication in civilian applications and for preventing unauthorized there is a need to develop a finger print recognition and analysis system. Fingerprint verification is an important biometric technique for personal identification. Biometrics are automated methods of recognizing an individual based on their physiological (e.g., fingerprints, face, retina, iris) or behavioral characteristics (e.g., gait, signature). Biometric-based solutions are able to provide for confidential financial transactions and personal data privacy. Each biometric has its strengths and weaknesses and the choice typically depends on the application. No single biometric is expected to effectively meet the requirements of all the applications. The match between a biometric and an application is determined depending upon the characteristics of the application and the properties of the biometric. Fingerprints are graphical flow-like ridges present on human fingers. They are fully formed at about seven months of fetus development and finger ridge configurations do not change throughout the life of an individual except due to accidents such as bruises and cuts on the fingertips. This property makes fingerprints a very attractive biometric identifier. Fingerprint system can be separated into two categories Verification and identification. Identification system recognizes an individual by searching the entire template database for a match. It conducts one-to-many comparisons to establish the identity of the individual. In an identification system, the system establishes a subject’s identity (or fails if the subject is not enrolled in the system database) without the subject having to claim an identity.
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2 Process Description Detailed Description of Fingerprint System The various steps involved in a typical fingerprint recognition system are shown below
Figure 1: Various steps in a Fingerprint system A finger print system works in two modes they are Enrollment mode and Authentication mode. Enrollment mode: fingerprint system is used to identify and collect the related information about the person and his/her fingerprint image. Authentication mode: fingerprint system is used to identify the person who is declared to be him/her.
Figure 2: Enrollment and Authentication stages of a fingerprint system
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Steps In The Design Process
Figure 3: Image Preprocessing and Feature Extraction
3 Resources and Limitations A prototype implementation of fingerprint recognition can be demonstrated by live real-time fingerprint authentication using a very small silicon fingerprint sensor(AuthenTec AES-4000) and a combination microcontroller with DSP development board. An overview of fully realized user identification functionality on an electronic device can be viewed as containing the following subsystems : (1) fingerprint sensor hardware, (2) a computational platform host, (3) biometric software, (4) system application software, and (5) user application software. These components are illustrated in the form of a architecture. The fingerprint detector detects the presence of a finger and converts the pattern into an electrical form that can be used by subsequent information processing stages. The biometric authentication services software manages and optimizes the sensor hardware, optimizes the fingerprint image, performs feature extraction and matching and makes decisions to accept or reject the identity. It is this layer that typically involves the heaviest computational workloads.
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The system application software is the link between the biometric identification system and the host device resources and operating systems. It provides host specific user interface and user control functions to the biometric ID system. It also allow biometric identification to be used to gain access to basic system resources. It performs functions like user login, applications and data protection and browser password replacement. • • • • •
Activates the sensor and detects the finger placed on the sensor. Collects images from the sensor and manages the user interaction from the sensor. Optimizes the images using various approaches Estimates the probability that the live images come from the same user as previously image stored data. Determines if the data stored offers sufficient match confidence to declare a verified user identity.
4 Conclusion By this project, we have represented the most promising technique for user authentication into any system securely. This technique now can be implemented using compute power that is presently available on modern DSPs (Digital Signal Processing). The use of such technology is dependent on our ability to integrate it into a system into a user friendly and most efficient manner.
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