Palm Scanner

Objective

Our objective is to propose a scanner-based personal authentication system by using the palm-print features. It is very suitable in many network-based applications. It involves comparing a user's biometric data to the previously recorded data for that person to ensure that this is the same person. Palm patterns are advantageous for this purpose because they are unique from one person to the next and except for the size, they do not change as the individual ages. The use of this technology would enable convenient biometric authentication for a wide range of applications such as safeguarding important information through log-in verification for access to sales, technical or personal data.

 

After implementing this project we expect to offer following services

 

  • Authenticate users to log them in to PCs and unlock the screen.
  • Permit access to various electronic devices.
  • Check identities at secure rooms upon entering or exiting.
  • Confirm attendance

Methedology

We propose a feature-based hierarchical framework for hand geometry recognition, based upon matching of geometrical and shape features. The authentication system consists of enrollment and verification stages. In the enrollment stage, the training samples are collected and processed by the pre-processing, feature extraction, and modeling modules to generate the matching templates.

In the verification stage, a query sample is also processed by the pre-processing and feature extraction modules, and then is matched with the reference templates to decide whether it is a genuine sample or not.

The reference templates for a specific user are generated in the modeling module. Last, we use the template-matching and the back propagation neural network to measure the similarity in the verification stage. Experimental results verify the validity of our proposed approaches in personal authentication.

In the first phase of the palm recognition process the area of the palm is located on the basis of the hand contour and the stable points. The extracted palm area is hexagonal. In the second phase the principal lines of the palm are extracted using line detection masks and a line-tracking algorithm. Finally, a live-template based on the principal palm lines is matched to the templates from the palm print database using an approach. The final decision about whether to accept or reject a user (does the person's identity match the claimed ID or PIN code) is made in the decision module. The figure or geometry of the palm is matched with the geometry of palm stored in the database. This unique matching score is compared to a predefined threshold and a decision about whether to accept or reject the person's authorization is made.

he use of this technology would enable convenient biometric authentication for a wide range of applications, such as safeguarding important information through log-in verification for access to sales, technical or personal data.

Technology Used

2.2  TECHNOLOGY USED:-                                              

Program modules for preprocessing the Palmprint images, template generation and palm recognition.

An example of  palm-area localization.

a)-Original image,

b)-Image after preprocessing,

c)-Extracted  palmcontour,

d)-Localized area of the palm (region of interest

In order to localize the palmarea, the first step is to preprocess the palmimages, this involves Gaussian smoothing and contrast enhancement. (Fig. a) is captured by a scanner, (Fig. b) shows the result of preprocessing. Standard global thresholding is used for the segmentation of the hand. After that, a contour-following algorithm is used to extract the hand contour (Fig. c). Based on the stable points on the contour, the palm area, which is approximated by a hexagonal area, is determined. ( Fig.d) presents the extracted region of interest.

Color Model

 RGB Color Space-

 The RGB color space consists of the three additive primaries: red, green and blue. Spectral components of these colors combine additively to produce a resultant color.

The RGB model is represented by a 3-dimensional cube with red green and blue at the corners on each axis (Figure 1). Black is at the origin. White is at the opposite end of the cube. The gray scale follows the line from black to white. In a 24-bit color graphics system with 8 bits per color channel, red is (255, 0, 0). On the color cube, it is (1, 0, 0).

The RGB model simplifies the design of computer graphics systems but is not ideal for all applications. The red, green and blue color

components are highly correlated.

This makes it difficult to execute some image processing algorithms. Many processing techniques, such as histogram equalization, work on the intensity component of an image only.

 

 

 

 

2.2.1.2 YCbCr Color Space-

 

YCbCr color space has been defined in response to increasing demands for digital algorithms in handling video information, and has since become a widely used model in a digital video.

It belongs to the family of television transmission color spaces. YCbCr is a digital color system,These color spaces separate RGB (Red-Green-Blue) into luminance and chrominance information and are useful in compression applications however the specification of colors is somewhat unintuitive.

The Recommendation 601 specifies 8 bit (i.e. 0 to 255) coding of YCbCr.

Following formula are use to calculate the valu of C Cb Cr-

Y  = 0.299 * R + 0.587 * G + 0.114 * B;

Cb = -0.169 * R - 0.332 * G + 0.500 * B;

Cr = 0.500 * R - 0.419 * G - 0.081 * B;

2.3 RELATED WORK:-

2.3.1 Biometric systems-

Biometrics refers to methods for uniquely recognizing humans based upon one or more intrinsic physical or behavioral traits. In information technology, in particular, biometrics is used as a form of identity access management and access control. It is also used to identify individuals in groups that are under surveillance.

Biometric characteristics can be divided in two main classes:

  • Physiological are related to the shape of the body. Examples include, but are not limited to fingerprint, face recognition, DNA, hand and palm geometry, iris recognition, which has largely replaced retina, and odor/scent.
  • Behavioral are related to the behavior of a person. Examples include, but are not limited to typing rhythm, gait, and voice. Some researchershave coined the term behaviometrics for this class of biometrics.

 

2.3.1.1 A biometric system can provide the following two functions:-

 

·        Verification-

Authenticates its users in conjunction with a smart card, username or ID number. The biometric template captured is compared with that stored against the registered user either on a smart card or database for verification.

·        Identification-

Authenticates its users from the biometric characteristic alone without the use of smart cards, usernames or ID numbers. The biometric template is compared to all records within the database and a closest match score is returned. The closest match within the allowed threshold is deemed the individual and authenticated.

Snapshots

Testing & Application

  White Box Testing

The purpose of any security testing method is to ensure the robustness of a system in the face of malicious attacks or regular software failures. White box testing is performed based on the knowledge of how the system is implemented. White box testing includes analyzing data flow, control flow, information flow, coding practices, and exception and error handling within the system, to test the intended and unintended software behavior. White box testing can be performed to validate whether code implementation follows intended design, to validate implemented security functionality, and to uncover exploitable vulnerabilities.

White box testing requires access to the source code. Though white box testing can be performed any time in the life cycle after the code is developed, it is a good practice to perform white box testing during the unit testing phase.

White box testing requires knowing what makes software secure or insecure, how to think like an attacker, and how to use different testing tools and techniques. The first step in white box testing is to comprehend and analyze available design documentation, source code, and other relevant development artifacts, so knowing what makes software secure is a fundamental requirement. Second, to create tests that exploit software, a tester must think like an attacker. Third, to perform testing effectively, testers need to know the different tools and techniques available for white box testing. The three requirements do not work in isolation, but together.

Typical white box test design techniques include:

    * Control flow testing

    * Data flow testing

    * Branch testing

 

 

 

 

 

 

7. APPLICATIONS:-

 

·         Majority of applications are in financial transactional authorization, physical access control, and PC logical access.

·         Security systems: physical admission into secured areas with door lock and integrated building security systems

·         Log-in control: Authenticate users to log them in to  network or PCs and unlock the screen. 

·         Healthcare: ID verification for medical equipment, electronic record management

·         Banking and financial services: access to ATM, kiosks, vault

·         Permit access to various electronic devices.

·         Obtain authorization for electronic transactions.

·         Check identities at secure rooms upon entering or exiting.

·         It save the administrative resources that were previously    dedicated to password management and password verification have many problems (people write them down, they forget them, they make up easy-to-hack passwords)

·         Your identity can be verified without resort to documents that may be stolen, lost or altered.

·         It provide safeguarding important information through log-in verification for access to sales, technical or personal data.

Hardware Requirement

 

8.  HARDWARE & SOFTWARE REQUIREMENTS

 

8.1 Hardware Requirement:-

·         Pentium based processor with minimum OS 500 MHz.

·         Hard Disk memory space of at least 15 GB and above.

·         256 MB of RAM and above.

·         Intel based motherboard.

8.2. Software Requirement:-

 

8.2.1 Front End:-

·        .Net Framework 2.0 and above.

  • C#.Net

8.2.2 Back End:-

SQL Server 2000 and above

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