ANSI INCITS ISO IEC TR 29794-5-2010 Information technology - Biometric Sample Quality - Part 5 Face image data (Technical Report).pdf

1、 INCITS/ISO/IEC TR 29794-5:2010 2015 (ISO/IEC TR 29794-5:2010, IDT) Information technology - Biometric Sample Quality - Part 5: Face image data (Technical Report) INCITS/ISO/IEC TR 29794-5:2010 2015 PDF disclaimer This PDF file may contain embedded typefaces. In accordance with Adobes licensing poli

2、cy, this file may be printed or viewed but shall not be edited unless the typefaces which are embedded are licensed to and installed on the computer performing the editing. In downloading this file, parties accept therein the responsibility of not infringing Adobes licensing policy. The ISO Central

3、Secretariat accepts no liability in this area. Adobe is a trademark of Adobe Systems Incorporated. Details of the software products used to create this PDF file can be found in the General Info relative to the file; the PDF-creation parameters were optimized for printing. Every care has been taken t

4、o ensure that the file is suitable for use by ISO member bodies. In the unlikely event that a problem relating to it is found, please inform the Central Secretariat at the address given below. Registered by INCITS (InterNational Committee for Information Technology Standards) as an American National

5、 Standard. Date of Registration: 2/1/2015 Published by American National Standards Institute, 25 West 43rd Street, New York, New York 10036 Copyright 2015 by Information Technology Industry Council (ITI). All rights reserved. These materials are subject to copyright claims of International Standardi

6、zation Organization (ISO), International Electrotechnical Commission (IEC), American National Standards Institute (ANSI), and Information Technology Industry Council (ITI). Not for resale. No part of this publication may be reproduced in any form, including an electronic retrieval system, without th

7、e prior written permission of ITI. All requests pertaining to this standard should be submitted to ITI, 1101 K Street NW, Suite 610, Washington DC 20005. Printed in the United States of America ii ITIC 2015 All rights reserved Reference numberISO/IEC TR 29794-5:2010(E)ISO/IEC 2010TECHNICAL REPORT IS

8、O/IECTR29794-5First edition2010-04-01Information technology Biometric sample quality Part 5: Face image data Technologies de linformation Qualit dchantillon biomtrique Partie 5: Donnes dimage de face ISO/IEC TR 29794-5:2010(E) PDF disclaimer This PDF file may contain embedded typefaces. In accordanc

9、e with Adobes licensing policy, this file may be printed or viewed but shall not be edited unless the typefaces which are embedded are licensed to and installed on the computer performing the editing. In downloading this file, parties accept therein the responsibility of not infringing Adobes licens

10、ing policy. The ISO Central Secretariat accepts no liability in this area. Adobe is a trademark of Adobe Systems Incorporated. Details of the software products used to create this PDF file can be found in the General Info relative to the file; the PDF-creation parameters were optimized for printing.

11、 Every care has been taken to ensure that the file is suitable for use by ISO member bodies. In the unlikely event that a problem relating to it is found, please inform the Central Secretariat at the address given below. COPYRIGHT PROTECTED DOCUMENT ISO/IEC 2010 All rights reserved. Unless otherwise

12、 specified, no part of this publication may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying and microfilm, without permission in writing from either ISO at the address below or ISOs member body in the country of the requester. ISO copyright off

13、ice Case postale 56 CH-1211 Geneva 20 Tel. + 41 22 749 01 11 Fax + 41 22 749 09 47 E-mail copyrightiso.org Web www.iso.org Published in Switzerland ii ISO/IEC 2010 All rights reservedISO/IEC TR 29794-5:2010(E) ISO/IEC 2010 All rights reserved iiiContents Page Foreword iv Introduction.v 1 Scope1 2 No

14、rmative references1 3 Terms and definitions .1 4 Abbreviated terms .1 5 Approaches to Face Image Quality .2 6 Categorization of Facial Quality.2 7 Facial Image Quality Analysis4 7.1 Dynamic Subject Characteristics 5 7.1.1 Subjects Behaviour 5 7.1.2 Analysis Based on Statistical Differences of the Le

15、ft and Right Half of the Face5 7.2 Static Characteristics of the Acquisition Process .7 7.2.1 Image Resolution and Size.8 7.2.2 Noise.8 7.3 Characteristics of Image Acquisition 8 7.3.1 Image Properties .8 7.3.2 Image Appearance.9 7.3.3 Illumination Intensity.9 7.3.4 Image Brightness 9 7.3.5 Image Co

16、ntrast 10 7.3.6 Exposure 11 7.3.7 Focus, Blur and Sharpness11 7.3.8 Colour .12 7.3.9 Subject-Camera distance12 Bibliography13 ISO/IEC TR 29794-5:2010(E) iv ISO/IEC 2010 All rights reservedForeword ISO (the International Organization for Standardization) and IEC (the International Electrotechnical Co

17、mmission) 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.

18、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,

19、ISO/IEC JTC 1. International Standards are drafted in accordance with the rules given in the ISO/IEC Directives, Part 2. The main task of the joint technical committee is to prepare International Standards. Draft International Standards adopted by the joint technical committee are circulated to nati

20、onal bodies for voting. Publication as an International Standard requires approval by at least 75 % of the national bodies casting a vote. In exceptional circumstances, the joint technical committee may propose the publication of a Technical Report of one of the following types: type 1, when the req

21、uired support cannot be obtained for the publication of an International Standard, despite repeated efforts; type 2, when the subject is still under technical development or where for any other reason there is the future but not immediate possibility of an agreement on an International Standard; typ

22、e 3, when the joint technical committee has collected data of a different kind from that which is normally published as an International Standard (“state of the art”, for example). Technical Reports of types 1 and 2 are subject to review within three years of publication, to decide whether they can

23、be transformed into International Standards. Technical Reports of type 3 do not necessarily have to be reviewed until the data they provide are considered to be no longer valid or useful. Attention is drawn to the possibility that some of the elements of this document may be the subject of patent ri

24、ghts. ISO and IEC shall not be held responsible for identifying any or all such patent rights. ISO/IEC TR 29794-5, which is a Technical Report of type 2, was prepared by Joint Technical Committee ISO/IEC JTC 1, Information technology, Subcommittee SC 37, Biometrics. ISO/IEC 29794 consists of the fol

25、lowing parts, under the general title Information technology Biometric sample quality: Part 1: Framework Part 4: Finger image data Technical Report Part 5: Face image data Technical Report ISO/IEC TR 29794-5:2010(E) ISO/IEC 2010 All rights reserved vIntroduction The purpose of this part of ISO/IEC 2

26、9794 is to define and specify methodologies for computation of objective, quantitative quality scores for facial images. Furthermore, the purpose, intent, and interpretation of face quality scores are defined. ISO/IEC 19794-5, Information technology Biometric data interchange formats Part 5: Face im

27、age data, already gives some specifications that are related to scene constraints of the facial images, photographic properties of the facial images, and digital image attributes of the facial images. Within this part of ISO/IEC 29794, a sample of a classification scheme of facial quality is exempli

28、fied and approaches for the determination of certain aspects of quality are introduced. TECHNICAL REPORT ISO/IEC TR 29794-5:2010(E) ISO/IEC 2010 All rights reserved 1Information technology Biometric sample quality Part 5: Face image data 1 Scope For aspects of quality specific to facial images, this

29、 part of ISO/IEC 29794: specifies terms and definitions that are useful in the specification, use and testing of face image quality metrics; defines the purpose, intent, and interpretation of face image quality scores. Performance assessment of quality algorithms and standardization of quality algor

30、ithms are outside the scope of this part of ISO/IEC 29794. 2 Normative references The following referenced documents are indispensable for the application of this document. For dated references, only the edition cited applies. For undated references, the latest edition of the referenced document (in

31、cluding any amendments) applies. ISO/IEC 29794-1, Information technology Biometric sample quality Part 1: Framework 3 Terms and definitions For the purposes of this document, the terms and definitions given in ISO/IEC 29794-1 and the following apply. 3.1 comparison score numerical value (or set of v

32、alues) resulting from a comparison 3.2 face quality assessment algorithm algorithm that computes a quality score for a given face image sample 3.3 facial image electronic image-based representation of the portrait of a person 4 Abbreviated terms CCD Charge-coupled device DCT Discrete Cosine Transfor

33、m ISO/IEC TR 29794-5:2010(E) 2 ISO/IEC 2010 All rights reservedGCF Global Contrast Factor FQAA Face Quality Assessment Algorithm QS Quality Score FQS Face Quality Score QSN Quality Score Normalization 5 Approaches to Face Image Quality Face Image Quality can be defined in many ways, depending on the

34、 application. For the purpose of this part of ISO/IEC 29794 standard Face Image Quality is defined in relation to the use of facial images with automated face recognition systems. The performance of an automated face recognition system is affected by the amount of defect or the degree of imperfectio

35、n present in the face image. The knowledge of quality can, and is currently being used to, process face images differently, by either invoking some image enhancement or normalization methods prior to feature extraction, invoking different matchers based on quality, or simply changing the threshold.

36、The use of face image quality assessment to enhance the overall performance of the system is increasing 3, 4, 5. A very important application of real-time quality analysis of faces is Face Recognition in Video, also referred to as Face in a Crowd, Recognition on the move, or Face at a Distance, e.g

37、21. This part of ISO/IEC 29794 shows some approaches for estimating Face Image Quality. The aim is to give the reader examples of assessment algorithms. Note, that these algorithms have pros and cons and no one algorithm is likely to be suitable for all facial images. Standardization of these algori

38、thms is out of scope of this part of ISO/IEC 29794. The following related work is being done in ISO/IEC JTC1 SC37 1, 2: ISO/IEC 29794-1 suggests the use of Quality Algorithm Identification (QAID), or Quality Score Percentile Rank upon standardization of a Quality Score Normalization Dataset (QSND).

39、This part of ISO/IEC 29794 adopts the following approach for face sample quality description: Specifying characterization of the facial quality and possible defects of face biometric samples in categorized aspects. Showing how FQAAs can be used to derive face quality scores (FQSs) related to specifi

40、c characteristics and associated possible defects. An FQAA typically analyzes a face sample locally at the pixel or feature level and fuses the local analysis results over a global region. An FQS evaluates one or more characteristics and associated potential defects, and provides an indicator of the

41、 quality. A typical approach of a system for generation of quality scores for facial images then takes the atomic FQSs generated by the FQAAs and combines them to a final quality score. The final quality score must predict performance metrics such as either false match or false non-match of an autom

42、atic facial image recognition. 6 Categorization of Facial Quality Different factors affect the quality of the facial image with respect to biometric systems performance. A successful recognition will be based on the biometric characteristics of the subject and a number of factors that influence thes

43、e characteristics such as variations (e.g. due to ageing) and the environmental conditions in the acquisition process: Influence of subjects characteristics on biometric performance, Influence of the acquisition process (including the capturing device) on biometric performance. ISO/IEC TR 29794-5:20

44、10(E) ISO/IEC 2010 All rights reserved 3This classification is not sufficient, as it does not distinguish between static and dynamic characteristics and properties: static subjects characteristics are related to anatomical characteristics of the subject, dynamic subject characteristics are related t

45、o subjects behaviour during the acquisition process, static properties of the acquisition process are related to physical properties of the capturing device and effects caused by the sample processing chain, dynamic properties of the acquisition process are related to environmental conditions during

46、 the capturing process. Table 1 shows a classification scheme that differentiates between the dynamic versus static properties as well as the subject versus the acquisition process characteristics affecting facial quality. Table 1 Characterization of Facial Quality Subject characteristics Acquisitio

47、n process Static Biological characteristics, like - anatomical characteristics (e.g. head dimensions, eye positions) - injuries and scars - ethnic group - impairment Other static characteristics - Heavy facial wears, such as thick or dark glasses - Makeup - Permanent jewellery Acquisition process an

48、d capture device properties, like - image enhancement and data reduction process - physical properties (e.g. image resolution and contrast) - optical distortions - static properties of the background, e.g. wallpaper - camera characteristics o sensor resolution - scene characteristics o geometric dis

49、tortion Dynamic Subject characteristics and behaviour, like - closed eyes - (exaggerated) expression - hair across the eye - head pose - subject posing (frontal / non frontal to camera) Scenery, like - dynamic characteristics of the background like moving objects - variation in lightning and related potential defects as o deviation from the symmetric lighting o uneven lighting on the