ISO/IEC 20027:2018

INTERNATIONAL ISO/IEC
STANDARD 20027
First edition
2018-07
Information technology — Guidelines
for slap tenprint fingerprintture
Titre manque
Reference number
©
ISO/IEC 2018
© ISO/IEC 2018
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ii © ISO/IEC 2018 – All rights reserved

Contents Page
Foreword .iv
Introduction .v
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Sensor hardware requirement . 2
5 Acquisition software . 2
5.1 Acquisition process . 2
5.2 User feedback . 2
5.3 Acquisition check . 3
5.4 Image processing . 3
5.4.1 Resolution . 3
5.4.2 Segmentation . 3
5.4.3 Compression . 4
6 Logging and evaluation of data . 4
6.1 Logging data . 4
6.2 Useful statistical evaluations . 5
7 Operational process . 5
7.1 General user guidance . 5
7.2 Acquisition process recommendations. 8
8 Operational issues .10
8.1 Placement recommendations . .10
8.2 Calibration recommendations .10
8.3 Cleaning recommendations .11
8.4 Operator recommendations .11
Annex A (informative) Example of an acquisition process .12
Annex B (informative) Example of an acquisition process based on composite records .13
Annex C (informative) Example of a quality assurance process for the build of a composite
record .15
Bibliography .16
© ISO/IEC 2018 – All rights reserved iii

Foreword
ISO (the International Organization for Standardization) and IEC (the International Electrotechnical
Commission) form the specialized system for worldwide standardization. National bodies that are
members of ISO or IEC participate in the development of International Standards through technical
committees established by the respective organization to deal with particular fields of technical
activity. ISO and IEC technical committees collaborate in fields of mutual interest. Other international
organizations, governmental and non-governmental, in liaison with ISO and IEC, also take part in the
work. In the field of information technology, ISO and IEC have established a joint technical committee,
ISO/IEC JTC 1.
The procedures used to develop this document and those intended for its further maintenance are
described in the ISO/IEC Directives, Part 1. In particular the different approval criteria needed for
the different types of document should be noted. This document was drafted in accordance with the
editorial rules of the ISO/IEC Directives, Part 2 (see www .iso .org/directives).
Attention is drawn to the possibility that some of the elements of this document may be the subject
of patent rights. ISO and IEC shall not be held responsible for identifying any or all such patent
rights. Details of any patent rights identified during the development of the document will be in the
Introduction and/or on the ISO list of patent declarations received (see www .iso .org/patents).
Any trade name used in this document is information given for the convenience of users and does not
constitute an endorsement.
For an explanation on the voluntary nature of standards, the meaning of ISO specific terms and
expressions related to conformity assessment, as well as information about ISO's adherence to the
World Trade Organization (WTO) principles in the Technical Barriers to Trade (TBT) see the following
URL: www .iso .org/iso/foreword .html.
This document was prepared by Technical Committee ISO/IEC JTC 1, Information technology,
Subcommittee SC 37, Biometrics.
This first edition cancels and replaces ISO/IEC TS 20027:2015, which has been technically revised.
The main changes compared to the previous edition are as follows:
— Clauses 2 and 3 have been added according to the ISO/IEC Directives, Part 2;
— in 5.2, a new example of ways to give feedback has been added.
Any feedback or questions on this document should be directed to the user’s national standards body. A
complete listing of these bodies can be found at www .iso .org/members .html.
iv © ISO/IEC 2018 – All rights reserved

Introduction
The slap tenprint capture process captures multiple slap images which contain all ten fingerprints.
Slap fingerprints, or “simultaneous plain impressions”, are simply multiple flat fingerprints captured at
the same time.
A single slap image contains four fingerprints from one hand, so two slap images contain eight
fingerprints.
A third slap image is captured containing the two thumbprints, so three slap images contain all ten
fingerprints.
© ISO/IEC 2018 – All rights reserved v

INTERNATIONAL STANDARD ISO/IEC 20027:2018(E)
Information technology — Guidelines for slap tenprint
fingerprintture
1 Scope
This document provides guidelines to follow during the acquisition process of slap tenprints in order to
obtain fingerprints of the best quality possible within acceptable time constraints.
Non-cooperative users are out of the scope of this document.
When using ten-fingerprint sensors, it is fundamental to know how to use them and how to proceed
with the acquisition. This document describes how to capture fingerprints correctly by specifying best
practices for slap tenprint captures.
It gives recommendations on the following topics:
1) hardware of the fingerprint sensor and its deployment;
2) user guidance;
3) enrolment process including a sample workflow;
4) application software for developers and system integrators;
5) processing, compression and coding of the acquired fingerprint images;
6) operational issues and data logging;
7) evaluation of a solution and its components.
Although this document primarily focuses on reaching optimal data quality for enrolment purposes,
the recommendations given here are applicable for other purposes. All processes which rely on good
quality tenprint slaps can take advantage of the best practices.
2 Normative references
The following documents are referred to in the text in such a way that some or all of their content
constitutes requirements of this document. For dated references, only the edition cited applies. For
undated references, the latest edition of the referenced document (including any amendments) applies.
ISO/IEC 2382-37, Information technology — Vocabulary — Part 37: Biometrics
3 Terms and definitions
For the purposes of this document, the terms and definitions given in ISO/IEC 2382-37 apply.
ISO and IEC maintain terminological databases for use in standardization at the following addresses:
— IEC Electropedia: available at http: //www .electropedia .org/
— ISO Online browsing platform: available at https: //www .iso .org/obp
© ISO/IEC 2018 – All rights reserved 1

4 Sensor hardware requirement
[6]
Image quality should comply with the quality specifications from ISO/IEC 19794-4. EBTS V 8.002:2008 ,
[5]
Annex F corresponds to ISO/IEC 19794-4:2011, B.1, and BSI TR-03121 corresponds to ISO/IEC 19794-
4:2011, B.2.
This document considers recommendations based on the experience of the use of fingerprint optical
sensors based on the principle of frustrated total internal reflection. The recommendations are to be
considered properly when considering the use of a new technology, as specificities of the technology
may induce specific recommendation that will be included in a future version of this document.
The sensor device should provide methods for re-calibration in the field by qualified service staff if the
device technically supports it.
The need for calibration or re-calibration depends on the sensor technology and calibration might not
be necessary for all devices.
The compliance of a sensor device to the applicable quality standard should be verified at any time in
the operational environment.
5 Acquisition software
5.1 Acquisition process
For the acquisition process, the highest quality images should be used. The acquisition of these images
should be done automatically. If the automatic acquisition process does not provide images of sufficient
quality, an alternative manual process may be activated. For example, after 3 captures of insufficient
quality, manual capture may be proposed to the operator.
The sequence of images having the highest quality should be used; if a timeout has occurred then these
may be below the desired quality levels. The best images may not be the last acquired.
Some devices support surface heating and may assist in better quality images where fingers are
especially dry.
An example of an acquisition process design can be found in Annex A and Annex B. An example of a
quality metric process design can be found in Annex C.
5.2 User feedback
The presence of a user interface is strongly advised to provide user feedback.
Feedback can be given, for example, by:
— a screen attached in close proximity to the sensor;
— illuminated pictograms on the sensor;
— LEDs assigned to pictograms directly on the sensor.
— Sound coming from the sensor or from the PC to which the sensor is connected.
The following information should be given to the user:
— assistance to finger positioning with images and/or video on the screen and/or audio instructions
(for instance to instruct the user to move their fingers to the left/right/top/bottom);
— visual and/or audio notification when a successful acquisition has been completed;
— a quality indicator for each acquisition; this indicator should follow the NIST fingerprint image
quality (NFIQ) measurement;
2 © ISO/IEC 2018 – All rights reserved

— if possible, the reason for a bad quality acquisition (e.g. wrong positioning of the hand).
Additional information (e.g. a poster or a video) can be used to illustrate to users how to use the system.
This information can be displayed close to the sensor and additionally in the waiting zone.
Operators should be trained to give guidance to the users.
5.3 Acquisition check
The software linked to the sensor should account for the following during the acquisition process in
order to perform a better acquisition:
— Any feedback provided by the sensor software (background correction, quality evaluation, end of
acquisition, etc.).
— A timeout for capturing the best available image in case the specified quality threshold is not
reached.
— The inability of the subject to provide a full set of fingerprints. Acceptable images for certain fingers
may not have been captured, which could be due to:
— missing fingers;
— inability for the subject to interact with the sensor correctly;
— temporary or permanent issues with the subject’s fingerprints.
— The image quality of the captured images. This is to enable the system to finish the acquisition
process after the preset quality level or a timeout has been reached.
— The subject’s fingers have been removed from the sensor at the end of the acquisition process.
— Check two consecutively captured slaps and captured thumbs are not identical. A duplicate check
should also be performed to ensure that all expected fingers have been captured once and once only.
NOTE Due to computational time constraints this recommendation can also be enforced by the operator
instead of the software.
— Residual traces have not been acquired.
— The fingerprint images are as originally acquired. Optionally, segmented images can be produced.
— Hand inversion between left and right slap has not occurred. This check can be based on the different
physical characteristics of the shapes of both hands.
5.4 Image processing
5.4.1 Resolution
Fingerprints should only be taken at 500 ppi or 1 000 ppi. Ideally scanning and transmission resolution
should be identical. However, if an image is captured at 1 000 ppi and is to be transmitted at 500 ppi,
then the guidance for down-sampling contained in the document NIST Special Publication 500-289
[1]
Compression Guidance for 1 000 ppi Friction Ridge Imagery should be followed in order to produce a
500 ppi image with the minimal effect on the image contents and quality.
5.4.2 Segmentation
Depending on the call to capture one, two, three or four fingerprints, this number of individual
fingerprints should be extracted from the input image and provided as single fingerprints generated by
a segmentation process which takes into account fingers reported to be missed.
© ISO/IEC 2018 – All rights reserved 3

For this segmentation process, the following criteria should be fulfilled:
— ability to accept rotated fingerprints having the same direction at an angle up to 45°;
— rotated fingerprints having the same direction should be corrected to be vertical;
— segment the first part over the finger (first phalanx);
— segmentation should be performed on uncompressed data;
— recording of any missing, damaged or amputated fingers.
Recommended size for fingerprint images is given in ISO/IEC 19794-4:2011, D.1.
NOTE Size limitation is done in order to prevent performance issues.
5.4.3 Compression
Wavelet Scalar Quantization (WSQ) compression should be used for 500 ppi images, and JPEG 2000
compression for 1 000 ppi images.
Fingerprint images should be compressed according to the recommendations in ISO/IEC 19794-
4:2011, 8.3.17.
The implementation of the WSQ algorithm used should be certified by a registered authority and
referenced as such (for example, the US Federal Bureau of Investigation and the respective certificate
number can both be coded in the WSQ header).
Multiple lossy compressions should be avoided as they degrade image quality.
6 Logging and evaluation of data
6.1 Logging data
The purpose of the logging data is not to track people but to give guidance to the staff in charge of the
enrolment and to maintain a constant quality of the acquisition process.
The following data, or parts of it, should be logged:
— transaction ID;
— timestamp of acquisition;
— duration of biometric acquisition process;
— number of captured images;
— number of successful captures;
— quality scores for all captured fingerprints;
— overall quality score of captured slap or tenprints sets (if present);
— information about vendor, software, hardware and versions;
— information about the origin (e.g. Agency Identifier);
— information about errors (e.g. about uniqueness check, segmentation, etc.);
— size of acquired data;
— testing flags (if applicable);
4 © ISO/IEC 2018 – All rights reserved

— demographic data on the subject (gender, age);
— record of any missing, damaged or amputated fingers.
NOTE It might be appropriate to have a regular logging workflow and an evaluation mode logging workflow
with more comprehensive logging data. The latter one could be used for regular or incident-based checks of the
whole process.
When used in a verification or identification scenario, it is recommended to
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