Abstract
A inner knuckle print identification system has been designed and developed. This work presents a new approach to authenticate people according to their finger textures. This proposed method consists of three stages. They are preprocessing, feature extraction and matching. In the first stage, noise is suppressed using an image filtering. In the second stage, features are extracted by local line binary pattern. Artificial neural network and support vector machine are used to provide an efficient matching algorithm for inner knuckle print authentication. After matching, the algorithm returns the best match for the given fingerprint parameters. The use of inner knuckle print in biometric identification has been the most widely used authentication system. A classification with an accuracy of 89% and 97% has been obtained by support vector machine and artificial neural network classifier.
Highlights
The personal authentication based on hand biometric traits has been widely used in most of the modern security applications due to its low cost in acquiring data, its reliability in verifying the individuals and its degree of acceptance by the user
Features are extracted by local line binary pattern
The algorithm returns the best match for the given fingerprint parameters
Summary
The personal authentication based on hand biometric traits has been widely used in most of the modern security applications due to its low cost in acquiring data, its reliability in verifying the individuals and its degree of acceptance by the user. Fingerprint, hand geometry, vein and finger knuckle print are samples of biometric systems based on hand [1,2]. One of the new approaches that is drawn attention of research is Inner Knuckle Print (IKP). IKP features like palmprint are divided in three categories of principal line, wrinkles and edges. IKP features are extracted from low resolution images. Edge features cannot be extracted from low resolution images, wrinkles and lines can be extracted. Each finger has three knuckles but second knuckle contains more lines and more complex pattern which is better for feature extraction. Uniqueness, universality and permanence are the three important aspects in biometrics system and research conducted in biometric systems based on IKP are shown that having these characteristics has brought good results
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