香港理工大学高分辨率的指纹(HRF) 数据库_图像处理_科研数据集

香港理工大学高分辨率的指纹(HRF) 数据库(The Hong Kong Polytechnic University

(PolyU)High-Resolution-Fingerprint (HRF)

Database)

数据介绍：

Fingerprint is the most widely used biometric characteristic for personal identification because of its uniqueness and stability over time. Most of the existing automatic fingerprint recognition systems (AFRS) use the minutia features on fingerprints, i.e. the terminations and bifurcations of fingerprint ridges, for recognition. Although they can achieve good recognition accuracy and have been used in many civil applications, their performance still needs much improvement when a large population is involved or a high security level is required. One solution to enhancing the accuracy of AFRS is to employ more features on fingerprints other than only minutiae. Fingerprint additional features, such as pores, dots and incipient ridges (see Fig. 1 for examples), are routinely used by experts in manual latent fingerprint matching. Some of these additional features, e.g. pores, require high resolution fingerprint images to reliably capture them. Thanks to the distinctiveness of these fingerpr

关键词：

高分辨率的指纹,香港理工大学,UGC/CRC,

High-Resolution-Fingerprint,PolyU,UGC/CRC,

数据格式：

IMAGE

数据详细介绍：

The Hong Kong Polytechnic University (PolyU)

High-Resolution-Fingerprint (HRF) Database

Overview:

Fingerprint is the most widely used biometric characteristic for personal identification because of its uniqueness and stability over time. Most of the existing automatic fingerprint recognition systems (AFRS) use the minutia features on fingerprints, i.e. the terminations and bifurcations of fingerprint ridges, for recognition. Although they can achieve good recognition accuracy and have been used in many civil applications, their performance still needs much improvement when a large population is involved or a high security level is required. One solution to enhancing the accuracy of AFRS is to employ more features on fingerprints other than only minutiae. Fingerprint additional features, such as pores, dots and incipient ridges (see Fig. 1 for examples), are routinely used by experts in manual latent fingerprint matching. Some of these additional features, e.g. pores, require high resolution fingerprint images to reliably capture them. Thanks to the distinctiveness of these fingerprint additional features and to the advent of high quality fingerprint imaging sensors, they have recently attracted increasing attention from researchers and practitioners working on AFRS.

Our team in the Biometrics Research Centre (UGC/CRC) of the Hong