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GB/T 33767.6-2018 English PDF

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GB/T 33767.6-2018: Information technology -- Biometric sample quality -- Part 6: Iris image data
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GB/T 38663   GB/T 37036.3   GB/T 37036.2   GB/T 33767.1   GB/T 33767.9   GB/T 33767.14   

Basic data

Standard ID GB/T 33767.6-2018 (GB/T33767.6-2018)
Description (Translated English) Information technology -- Biometric sample quality -- Part 6: Iris image data
Sector / Industry National Standard (Recommended)
Classification of Chinese Standard L71
Classification of International Standard 35.240.15
Word Count Estimation 30,339
Date of Issue 2018-06-07
Date of Implementation 2019-01-01
Issuing agency(ies) State Administration for Market Regulation, China National Standardization Administration

GB/T 33767.6-2018: Information technology -- Biometric sample quality -- Part 6: Iris image data

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Information technology--Biometric sample quality--Part 6. Iris image data ICS 35.240.15 L71 National Standards of People's Republic of China Information Technology Biometric Sample Quality Part 6. Iris Image Data Part 6. Irisimagedata (ISO /IEC 29794-6.2015, IDT) Published on.2018-06-07 2019-01-01 Implementation National Market Supervision Administration China National Standardization Administration released Directory Preface I Introduction II 1 Scope 1 2 Compliance 1 3 Normative references 1 4 Terms and Definitions 2 5 Abbreviations 3 6 iris image quality indicator 3 7 iris acquisition quality 14 8 Iris Image Quality Data Record 17 Appendix A (Normative) Compliance Test Statement 21 Appendix B (Informative) Iris Image Quality 22 Reference 26

Foreword

GB/T 33767 "Information Technology Biometric Sample Quality" is currently divided into the following sections. --- Part 1. Frameworks; --- Part 4. Fingerprint image data; --- Part 5. Face image data; --- Part 6. Iris image data. This section is part 6 of GB/T 33767. This section was drafted in accordance with the rules given in GB/T 1.1-2009. This section uses the translation method equivalent to the use of ISO /IEC 29794-6.2015 "Information Technology Biometric Sample Quality Part 6. Iris Image Data (English version). The Chinese documents that are consistent with the normatively quoted international documents in this section are as follows. --- GB/T 33767.1-2017 Quality of Information Technology Biometric Samples Part 1. Framework (ISO /IEC 29794-1. 2009, IDT) Please note that some of the contents of this document may involve patents. The issuing agency of this document does not assume responsibility for identifying these patents. This part is proposed and managed by the National Information Technology Standardization Technical Committee (SAC/TC28). This section was drafted by. China Electronic Technology Standardization Institute, Guangzhou Guangdian Zhuozhi Intelligent Technology Co., Ltd. Guangzhou Guangdian Express Gold Rong Electronics Co., Ltd., Shanxi Tiandi Technology Co., Ltd., Beijing Tiancheng Shengye Technology Co., Ltd., Shenzhen Aikui Intelligent Technology Co., Ltd. Division, Xi'an Kaihong Electronic Technology Co., Ltd., Zhejiang Ant Micro Finance Services Group Co., Ltd., Beijing Zhongke Hongba Technology Co., Ltd. Division, Shanghai Juhong Optoelectronics Technology Co., Ltd., Hangzhou Haoyuan Data Security Technology Co., Ltd., Guangdong Guangzhen Optoelectronics Technology Co., Ltd., Shenzhen Saixi Information Technology Co., Ltd. The main drafters of this section. Gao Jian, Huang Yuezhen, Lin Guanchen, Yuan Zhen, Liang Tiancai, Peng Cheng, Wang Wenfeng, Qin Rizhao, Yan Jianmin, Jin Xiaofeng, Nie Hao, Chen Xing, Sun Ye, Zhang Liexi, Zhang Monan, He Zhaofeng, Li Xingguang, Lin Chuan, Yue Xuyao, Gong Wenchuan, Liu Bing, Xu Jun, Gong Yazhuo, Tian Ye, Zhao Na, Wen Yishu, and Ke Wenhui.

Introduction

A method for evaluating the quality of a biometric sample by calculating a quality index to predict recognition under a given biometric identification system Accuracy. If used properly, quality indicators help improve the functionality of the biometric system. For example, in the registration or identification process, it They can reflect the integrity of the collected biometric data. This section is used to define terminology and quantification methods related to characterization of iris image data quality, and to evaluate them for high confidence in output Degree of potential for biometric matching decisions. GB/T 30267.1 and GB/T 28826.1 add a quality field and specify a quality that is suitable for a definitive iris image Range of scores. Annex B in GB/T 26237.6 describes the collection of iris image data and guidance on image quality. Do not However, these standards do not address the quantitative composition or interpretation of iris image quality indicators. This section is supported by authoritative experience data. The range of values for the relevant variable. In other cases, the range of values of the relevant variables is considered non-normative. The first five chapters of this section are. scope, compliance, normative references, terms and definitions, and abbreviations. Chapter 6 presents a The series is used to evaluate the quality index of the iris image quality. The impact of some indicators on the recognition rate has been quantified and clearly defined as normative; other means For reference only, it is used to provide valuable information for the follow-up work of the biometric identification system. Some of the indicators introduced in Chapter 6 apply to For single image analysis, some indicators apply to the quality comparison of two images (collected from the same eye). Chapter 7 defines the generation of compliance The quality parameters required for the iris image provide guidance for the acquisition equipment manufacturer. Chapter 8 presents the coding of iris image quality data records method. Information Technology Biometric Sample Quality Part 6. Iris Image Data

1 Scope

This part of GB/T 33767 specifies the following. ---Method for quantifying iris image quality; --- Specification requirements for hardware and software for generating iris images; --- Normative requirements for hardware and software to measure the availability of iris images; --- Terms and definitions used to quantify iris image quality; --- Standardized coding of iris image quality. This section does not apply to the performance evaluation of specific iris image quality assessment algorithms. Appendix A of this section indicates the applicable to this section Compliance test methods, test statements, and test procedures.

2 Compliance

When the measurement values required by 6.2.X.3 meet the effective range or threshold specified in 6.2.X.4, the iris image shall be considered fully usable. When two images acquired from an iris meet the requirements of 6.4, specifically when they are calculated using the method described in 6.4.X.3 The two iris images shall be considered fully usable when the effective range or threshold specified in 6.4.X.4 is sufficient. When the structure and data values of the iris image quality records meet the format requirements specified in Chapter 8 (Iris image quality data records) and its When the mass value is calculated by the method described in 6.2.X.3, the iris image quality record should be considered as meeting the criteria of this section. If you meet the 8th The normative requirements set forth in the chapter indicate that the first and second conformance requirements defined in Appendix A of ISO /IEC 19794-1.2011 are met; In accordance with the normative requirements of 6.2.X.3, it means that the three-level conformance requirements defined in Appendix A of ISO /IEC 19794-1.2011 are met. If the collection equipment meets the regulatory requirements described in chapter 7, the equipment complies with this part. The calculation of iris image availability shall comply with the requirements of 6.2, which is specifically the calculation method described in 6.2.X.3. Paired image availability The calculation shall be evaluated in accordance with the normative requirements of 6.4, specifically the calculation method described in 6.4.X.3. If the quality of one or more quality indicators in the implementation of this indicator is unacceptable (low quality), the target should be re-acquired. The other image data until. --- Capture fully compliant images; or ---Confirm that in the applicable limited time, repeat acquisition can still not obtain satisfactory quality (eg correct registration). under these circumstances, Select a non-conforming image as the best possible candidate image.

3 Normative references

The following documents are indispensable for the application of this document. For dated references, only dated versions apply to this article Pieces. For undated references, the latest version (including all amendments) applies to this document. ISO /IEC 19785-2 Information technology public biometric exchange format framework Part 2. Biometric registration machine Construction Techniques (Informationtechnology-Commonbiometricexchangeformatsframework-Part 2. Pro- Ceduresfortheoperationofthebiometricregistrationauthority) ISO /IEC 19794-1.2011 Information technology biometrics data exchange format Part 1. Framework (Information

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