A Fast and Accurate Palmprint Recognition System Based on Minutiae

Abstract

Palmprint recognition is a challenging problem, mainly due to low quality of the pattern, large nonlinear distortion between different impressions of the same palm and large image size, which makes feature extraction and matching computationally demanding. This paper introduces a high-resolution palmprint recognition system based on minutiae. The proposed system follows the typical sequence of steps used in fingerprint recognition, but each step has been specifically designed and optimized to process large palmprint images with a good tradeoff between accuracy and speed. A sequence of robust feature extraction steps allows to reliably detect minutiae; moreover, the matching algorithm is very efficient and robust to skin distortion, being based on a local matching strategy and an efficient and compact representation of the minutiae. Experimental results show that the proposed system compares very favorably with the state of the art.

Design & Implementation of Fingerprint Biometrics based on Discretized Fingerprint Texture Descriptor

“…With the help of the first step, the second stage filter, i.e., a frequency bandpass filter that was separable in the radial-and angular-frequency domains was employed. An experimental result showed that our proposed algorithm was able to handle various input image contexts and achieves better results compared with some stateof-the-art algorithms over public databases, and to improve the performances of fingerprint-authentication systems Some [5] proposed a high-resolution palm print recognition system based on minutiae. The proposed system followed the typical sequence of steps used in fingerprint recognition, but each step had been specifically designed and optimized to process large palm print images with a good trade-off between accuracy and speed.…”

Design & Implementation of Adaptive Fingerprint Biometrics with Training of DataSet

“…With the help of the first step, the second stage filter, i.e., a frequency band-pass filter that was separable in the radial-and angular-frequency domains was employed. An experimental result showed that our proposed algorithm was able to handle various input image contexts and achieves better results compared with some state-of-the-art algorithms over public databases, and to improve the performances of fingerprintauthentication systems Some [5] proposed a high-resolution palm print recognition system based on minutiae. The proposed system followed the typical sequence of steps used in fingerprint recognition, but each step had been specifically designed and optimized to process large palm print images with a good trade-off between accuracy and speed.…”

“…Image processing is used to resolve identification problems, such as in scientific medicine or in creating weather maps from satellite pictures. Although large-scale image processing systems still are being sold for massive imaging applications, such as handling of satellite images, the tendency continues toward diminishing and blending of general -purpose small computers with specified image processing hardware [5]. Skin on human fingertips contains ridges and valleys which together forms distinctive patterns.…”

Towards Regional Fusion for High-Resolution Palmprint Recognition

“…Though a high resolution palmprint image, as shown in Figure 1, is deemed to have rich types of features such as minutiae, principal lines, and pores, available high resolution palmprint matching algorithms [1]- [3] essentially follow the minutiae-based fingerprint matching strategy and focus on fullto-full/partial-to-full palmprint comparison. These algorithms would face problems when they are applied to forensic palmprint recognition where latent marks have much smaller area than full palmprints, which was also argued in a recent work on forensic palmprint recognition [4].…”