THESIS ON PALMPRINT RECOGNITION

The work investigates the theoretical concepts behind palmprint and finger knuckle print recognition and proposes new algorithms to extract features for recognition systems able to identify a person from a test sample with a strong degree of confidence. Abstract Palmar flexion crease matching is a method for verifying or establishing identity. So, during the template generation, the encrypted palmprint sub-images are first decrypted and then the features are extracted. As a small central part of the palmprint image is used for this purpose, so it is important to find that region of interest. From these comparisons, using manual palmar flexion crease identification, results showed that when labelled within 10 pixels, or 3.

JavaScript is disabled for your browser. This is inspired by using the completed local binary pattern, termed the dynamic threshold CLBP, which employs only the sign and magnitude components. After making a selection, click one of the export format buttons. To this end, this thesis describes new methods of manual and automated palmar flexion crease identification, that can be used to identify palmar flexion creases in online palmprint images. As biometric systems are vulnerable to replay, database and brute-force attacks, such potential attacks must be analyzed before they are massively deployed in security systems. Cast your vote You can rate an item by clicking the amount of stars they wish to award to this item. To select a subset of the search results, click “Selective Export” button and make a selection of the items you want to export.

Downloads per month over past year. The aim of the project was to analyze the performance of SIFT on palmvein patterns palmprinh the palmprint to know which is more secure because even though both the metrics are extracted from the same region it is difficult to forge the palmvein pattern when compared to palm print.

Finally, a new feature set is developed for finger knuckle print recognition. Different formats are available for download.

A Secure Template Generation Scheme for Palmprint Recognition Systems – ethesis

So, during the template generation, the encrypted palmprint sub-images are first decrypted and then the features are extracted.

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Providing authorized users with secure access to the services is a challenge to the personal identification systems. Along with security, also the privacy of the users is an important factor as the constructions of lines in palmprints contain personal characteristics. These drawbacks cause a great loss to the concerned. Securing the information has been a major issue now a days and depending on the requirements and security reasons most of the authentication systems are moved from passcodes, pass cards to biometric systems where the metrics are derived from human features.

The third contribution is related to a novel feature extraction method applied for use in palmprint and Finger Knuckle Print recognition.

Metadata Show full item record. To this end, this thesis describes new methods of manual and automated palmar flexion crease identification, that can be used to identify palmar flexion creases in online palmprint images.

Type Thesis or dissertation.

thesis on palmprint recognition

Biometric person recognition systems are increasingly being used to enhance the security of physical and logical security systems.

Cast your vote You can rate an item by clicking the amount of stars they wish to award to this item. The amount of items that will be exported is indicated in the bubble next to export format. Finger Knuckle Print and Palmprint for efficient person recognition.

To select a subset of the search results, click “Selective Export” button and make a selection of the items you want to export. Abstract Palmar flexion crease matching is a method for verifying or establishing identity.

Doctoral thesis, Northumbria University. The work investigates the theoretical concepts behind palmprint and finger knuckle print recognition and proposes new pa,mprint to extract features for recognition systems able to identify a person from a test sample with a strong degree of confidence.

A Secure Template Generation Scheme for Palmprint Recognition Systems

We propose a cryptographic approach to encrypt the palmprint images by an advanced Hill cipher technique for hiding the information on the palmprints.

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By default, clicking on the export buttons will result in a download of the allowed maximum amount of items. To achieve this Fibonacci numbers have been used to generate a distribution of binary codes at every pixel position in order to create descriptors that are more robust against lighting variations of images. From these comparisons, using manual palmar thwsis crease identification, results showed that when labelled within 10 pixels, or 3. As a small central part of the palmprint image is used for this purpose, so it is important to find that region of interest.

thesis on palmprint recognition

New methods of palmprint identification, that complement existing identification strategies, or reduce analysis and comparison times, will benefit palmprint identification communities worldwide. It also provides security to the palmprint images from being attacked by above mentioned attacks. To export the items, click on the button corresponding with the preferred download format.

The amount of items that can be exported at once is similarly restricted as the full export. Year Subject Department Author Type.

Finger Knuckle Print and Palmprint for efficient person recognition

The fifth contribution proposes a novel Fibonacci sequence local binary pattern descriptor and multi-scale Fibonacci sequence local binary pattern descriptor by carefully modifying the operator thresholding scheme at the pixel values.

Furthermore, in the second instance, a new method of automated palmar flexion crease recognition, that can be used to identify palmar flexion oon in online palmprint images, is described.

thesis on palmprint recognition

Palmprint can be one of the biometrics, used for personal identification thedis verification. In the second data set, that is, for images from palms, an equal error rate of 0.