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 Kong Polytechnic University has developed a high resolution fingerprint imaging device and has used it to constructed large-scale high resolution fingerprint databases (HRF). We intend to publish our database to facilitate researchers designing effective and efficient algorithms for extracting and matching fingerprint additional features.

Fig. 1: Example additional features on fingerprints, pores, dots, and incipient ridges.

Description of the PolyU HRF Database:

An optical fingerprint imaging device (see Fig. 2) has been built by our team. Its resolution is around 1,200dpi, and it can capture fingerprint images of various sizes, e.g. 320*240 pixels and 640*480 pixels.

(a)                                                                        (b)

Fig. 2: (a) The high resolution fingerprint imaging device we developed and (b) its inner structure.

Two high resolution fingerprint image databases (denoted as DBI and DBII) have been set up by using the developed fingerprint imaging device. DBI consists of a small training dataset and a large test dataset. The images of the same finger in both databases were collected in two sessions which were separated by about two weeks. Each image is named as ID_S_X. ID represents the identity of the person. S represents the session of the captured image. X represents the image number of each session. The following table gives the detailed information of the databases.

Database

Resolution

Image Size

#Fingers

#Images per finger per session

#Images

DBI: Training

~1,200dpi

320*240

35

3

210

DBI: Test

~1,200dpi

320*240

148

5

1,480

DBII

~1,200dpi

640*480

148

5

1,480

 

We labeled the ground truth of sweat pores in 30 images selected from DBI. The central coordinates (row, col) of each pore were wrote into a text file (.txt). The ground truth of dots and incipients of 48 selected images were also offered. The central coordinates (row, col) of dots and two ends of each incipient were wrote into a text file (.txt). Here, the 48 selected images consists of 2 set of images ("SetIGroundTruthSampleimage" and "SetIIGroundTruthSampleimage") captured in two sessions. All of the original sample images and text files are contained in "Ground Truth.zip".

 

Related Publication:

1.    Qijun Zhao, David Zhang, Lei Zhang, and Nan Luo, "Adaptive Fingerprint Pore Modeling and Extraction," Pattern Recognition, vol. 43(8), pp. 2833-2844, 2010

2.    Qijun Zhao, David Zhang, Lei Zhang, and Nan Luo, "High Resolution Fragmentary Fingerprint Alignment Using Pore-Valley Descriptors," Pattern Recognition, vol. 43, pp. 1050-1061, 2010

3.    Qijun Zhao, Lei Zhang, David Zhang, Nan Luo, and Jing Bao, “Adaptive Pore Model for Fingerprint Pore Extraction,” IAPR 19th International Conference on Pattern Recognition (ICPR2008), 2008

4.    Qijun Zhao, Lei Zhang, David Zhang, and Nan Luo, “Direct Pore Matching for Fingerprint Recognition,” IAPR/IEEE 3rd International Conference on Biometrics (ICB2009), pp. 597-606, 2009

5.    David Zhang, Feng Liu, Qijun Zhao, Guangming Lu, and Nan Luo, "Selecting a Reference High Resolution for Fingerprint Recognition Using Minutiae and Pores," IEEE Transactions on Instrumentation and Measurement, to appear

6.    Qijun Zhao, Feng Liu, Lei Zhang, and David Zhang, "A Comparative Study on Quality Assessment of High Resolution Fingerprint Images," Proceedings of the IEEE International Conference on Image Processing (ICIP2010), Hong Kong, September 2010

7.    Qijun Zhao, Feng Liu, Lei Zhang, and David Zhang, "Parallel versus Hierarchical Fusion of Extended Fingerprint Features," Proceedings of the IAPR 20th International Conference on Pattern Recognition (ICPR'10), Istanbul, Turkey, August 2010

8.    Feng Liu, Qijun Zhao, Lei Zhang, and David Zhang, "Fingerprint Pore Matching based on Sparse Representation," Proceedings of the IAPR 20th International Conference on Pattern Recognition (ICPR'10), Istanbul, Turkey, August 2010

9.    Q. Zhao, Lei Zhang, David Zhang, Wenyi Huang, and Jian Bai, “Curvature and Singularity Driven Diffusion for Oriented Pattern Enhancement with Singular Points,” CVPR09. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1-7, Miami, Florida, USA, June 22-24 2009.

The Announcement of the Copyright

All rights of the PolyU HRF Database are reserved. The database is only available for research and noncommercial purposes. Commercial distribution or any act related to commercial use of this database is strictly prohibited. A clear acknowledgement should be made for any public work based on the PolyU HRF Database. A citation to "PolyU HRF Database, http://www.comp.polyu.edu.hk/~biometrics/HRF/HRF.htm and our related works must be added in the references.

 

Downloading Steps (Recommend to open by IE):

The HRF database, including “HRF DBI.zip”, “HRF DBII.zip”, and "Ground Truth.zip", is made publicly available and can be obtained from this website. It is totally free for academic, noncommercial purposes. Any person or organization that wishes to use the database must agree to the terms of the agreement and fill in the agreement forms. The request confirmation will be sent by an email and the successful applicants will receive their login accounts and passwords to download the database.

Copyright © 2013   Biometric Research Center, The Hong Kong Polytechnic University