User’s Guide

Data

This package is part of the signal-processing and machine learning toolbox Bob. It contains an interface for the PUT Vein Dataset. This package does not contain the original data files, which need to be obtained through the link above.

The vein pattern recognition is one of the most promising and intensively developing field of studies in biometrics research. One of main obstacles in creating new methods of segmentation and classification of vein patterns was a lack of benchmarking dataset that would allow to obtain comparable results. Put Vein Database was created to overcame this problem and crate common platform for algorithms comparison.

PUT Vein pattern database is free available for research purposes can be applied as common platform for evaluation and comparison of new segmentation and classification algorithms. Enabling comparison of algorithms without different hardware systems used by researchers will help to chose the best algorithm, thus helping in biometrics systems design.

PUT Vein pattern database consists of 2400 images presenting human vein patterns. Half of images contains a palmar vein pattern (1200 images) and another half contains a wrist vein pattern (another 1200 images). Data was acquired from both hands of 50 students, with means it has a 100 different patterns for palm and wrist region. Pictures ware taken in 3 series, 4 pictures each, with at least one week interval between each series. In case of palm region volunteers ware asked to put his/her hand on the device to cover acquisition window, in way that line below their fingers coincident with its edge. No additional positioning systems ware used. In case of wrist region only construction allowing to place palm and wrist in comfortable way was used to help position a hand.

In this implementation we use both - original 50 client x 2 hand data - in the database clients with IDs between 1 and 50 - and also – mirrored file representations (left hand / palm data mirrored to look like right hand data and vice versa) - clients with IDs between 51 and 100.

Protocols

Each protocol of the PUTVEIN database consists of the following groups and purposes:

groups	world	dev	eval
purposes	train	enroll / probe	enroll / probe

Currently (as on 08.02.2017) there are 10 protocols:

• L_4,

• R_4,

• LR_4,

• RL_4,

• R_BEAT_4,

• L_1,

• R_1,

• LR_1

• RL_1,

• R_BEAT_1.

Protocols (except the BEAT protocols) still contains the original protocol (‘L’, ‘R’, ‘LR’, ‘RL’) data, the difference is, whether each enroll model is constructed using all 4 hand’s images (protocol name ends with 4), or each enroll image is used as a model (corresponding protocol names ends with 1).

The original protocols consists of following data, world purpose dataset consists of the same data, as dev purpose dataset, so won’t be separately described:

protocol	dev	eval
L	IDs 1-25, un-mirrored left hand images	IDs 26-50, un-mirrored left hand images
R	IDs 1-25, un-mirrored right hand images	IDs 26-50, un-mirrored right hand images
RL	IDs 1-50, un-mirrored right hand images	IDs 51-100, mirrored left hand images (to represent right hand)
LR	IDs 1-50, un-mirrored left hand images	IDs 51-100, mirrored right hand images (to represent left hand)

The new test protocols R_BEAT_1 and R_BEAT_4` are intended for use with ``bob.bio.vein and BEAT platform for quick tests, if necessary. Both protocols consist of such data:

protocol	dev	eval
R_BEAT	IDs 1, 2, un-mirrored right hand images	IDs 26, 27, un-mirrored right hand images

Please find additional information about protocols there:

1. bob.db.putvein.Database.objects()