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Basic dataStandard ID: GB/T 33767.1-2025 (GB/T33767.1-2025)Description (Translated English): Information technology - Biometric sample quality - Part 1: Framework Sector / Industry: National Standard (Recommended) Classification of Chinese Standard: L71 Classification of International Standard: 35.240.15 Word Count Estimation: 34,387 Date of Issue: 2025-08-01 Date of Implementation: 2026-02-01 Older Standard (superseded by this standard): GB/T 33767.1-2017 Issuing agency(ies): State Administration for Market Regulation, Standardization Administration of China GB/T 33767.1-2025: Information technology - Biometric sample quality - Part 1: Framework---This is an excerpt. Full copy of true-PDF in English version (including equations, symbols, images, flow-chart, tables, and figures etc.), auto-downloaded/delivered in 9 seconds, can be purchased online: https://www.ChineseStandard.net/PDF.aspx/GBT33767.1-2025ICS 35.240.15 CCSL71 National Standard of the People's Republic of China Replaces GB/T 33767.1-2017 Information Technology Biometric Sample Quality Part 1.Framework Part 1.Framework (ISO /IEC 29794-1.2024, IDT) Released on August 1, 2025 Implementation on February 1, 2026 State Administration for Market Regulation The National Standardization Administration issued Table of ContentsPreface III Introduction V 1 Scope 1 2 Normative references 1 3 Terms and Definitions 1 4 Abbreviations 4 5 Compliance 4 6 Biometric Sample Quality Criteria 4 6.1 Reference Model 4 6.2 Quality Aspects. Quality, Fidelity, and Utility 5 6.3 Use Cases for Data Quality Metrics 6 7 Data Interchange Format Field Definition 8 7.1 Abstract Description 8 7.2 XML Encoding 10 7.3 Labeled Binary Code 10 8 Exchange of Quality Assessment Algorithm Results 10 9 Quality Score Normalization11 10 Pair Quality 11 11 Evaluation 12 11.1 Overview 12 11.2 Mismatch Error and Discard Method 12 11.3 Mismatch Error and Discard Method 13 11.4 DET and discarding methods 14 11.5 Sample Acceptance or Rejection Rate 14 Appendix A (Informative) Biometric Quality Block Coding Example 16 Appendix B (Informative) Example of standardized exchange of quality assessment algorithm results 17 Appendix C (Informative) Aggregation of Utility-Based Quality Scores in Sample-Based Systems 20 Appendix D (Informative) Example Code for Calculating Utility Prediction Performance Indicators 22 Reference 25 Preface This document is in accordance with the provisions of GB/T 1.1-2020 "Guidelines for standardization work Part 1.Structure and drafting rules for standardization documents" Drafting. This document is Part 1 of GB/T 33767 “Quality of Information Technology Biometric Samples”. Lower part. --- Part 1.Framework; --- Part 4.Fingerprint image data; --- Part 5.Face image data; --- Part 6.Iris image data; --- Part 9.Vascular image data; --- Part 14.DNA data. This document replaces GB/T 33767.1-2017 "Information technology biometric sample quality Part 1.Framework" and GB/T 33767.1- Compared with.2017, in addition to structural adjustments and editorial changes, the main technical changes are as follows. a) Added "Quality score aggregation method" and "Quality assessment algorithm efficiency evaluation method" to the scope, and deleted "Specifies "Format and location of quality data fields in biometric data exchange formats" (see Chapter 1, Chapter 1 of the.2017 edition); b) Added terms and definitions. "biometric correlation characteristics", "biometric utility", "false mismatch error and discard characteristics", "false match Error and discard characteristics”, “Native quality metrics”, “Quality assessment algorithms”, “Quality components”, “Quality metrics” (see Chapter 3); c) Deleted the terms and definitions "biometric login failure", "biometric login failure rate", "feature", "non-inherent", and "inherent" “obtain failure rate”, “operator”, “sample”, “source”, “utility” (see Chapter 4 of the.2017 edition); d) The term “quality score” in the Terms and Definitions is changed to “quality score” (see Chapter 3, Chapter 4 of the.2017 edition); e) Added the abbreviations CDF, DET, FMR, and QVID (see Chapter 4); f) The abbreviations BIR and XML have been deleted (see Chapter 5 of the.2017 edition); g) Deleted “Universal Biometric Identification System” (see Chapter 6 of the.2017 edition); h) Added the use cases of data quality metrics "Quality-oriented fusion" (see 6.3.8) and "Reducing workload through quality scores" (see 6.3.10), “Selecting the best sample from a series of biometric samples” (see 6.3.11); i) Added "abstract description" to the data exchange format field definition (see 7.1); j) Added "Exchange of Quality Assessment Algorithm Results" (see Chapter 8), "Pairwise Quality" (see Chapter 10), and "Evaluation" (see Chapter 11). This document is equivalent to ISO /IEC 29794-1.2024 "Information technology — Biometric sample quality — Part 1.Framework". The following minimal editorial changes have been made to this document. ---Added additional information "Note 4.If the algorithm supplier is registered with the domestic biometric identification registration agency, use GB/T 28826.2 Allocating identifiers related to quality assessment algorithms” (see 7.1.2). Please note that some of the contents of this document may involve patents. The issuing organization of this document does not assume the responsibility for identifying patents. This document was proposed and coordinated by the National Technical Committee for Information Technology Standardization (SAC/TC28). This document was drafted by. Beijing Yanshen Intelligent Technology Co., Ltd., China Electronics Technology Standardization Institute, Lenovo Zhongtian Technology Co., Ltd. Co., Ltd., Shanxi Sanyouhe Smart Information Technology Co., Ltd., GRG Banking Group Co., Ltd., China Electronics Technology Standardization Institute East China Branch, Shanghai SenseTime Intelligent Technology Co., Ltd., Guangzhou GRG Intelligent Technology Co., Ltd., Beijing University of Civil Engineering and Architecture, Beijing Wanlihongke Technology Co., Ltd., Rockwell Automation Group Co., Ltd., Institute of Automation, Chinese Academy of Sciences, Changchun Boli Electronic Technology Co., Ltd., Xiamen University, Mashang Consumer Finance Co., Ltd., Guangdong Jiulian Technology Co., Ltd., Xiamen Ruiwei Information Technology Co., Ltd., Shengdian Century Technology Co., Ltd., Taiyuan Rockwell Automation Co., Ltd., Beijing Deyi Audio Communication Technology Co., Ltd., Shengshi Technology Co., Ltd. Co., Ltd., Shenzhen Yuntianlifei Technology Co., Ltd. The main drafters of this document are. Wang Shuqi, Geng Li, Li Wei, Xi Yafen, Su Liwei, Song Jiwei, Peng Cheng, Zhang Menan, Pan Xiaoguang, Liu Yao, Zhou Yang, Yang Chunlin, Zhang Xiaoliang, Yang Xu, Zhang Wei, Jiang Hui, Jie Yongsheng, Wu Changhao, Zeng Qingning, Li Qi, Hu Jianliang, Wang Yunlong, Zhang Lihua, Guo Maozu, Tian Qichuan, Li Xiaochao, Zeng Dingheng, Ling Jun, He Yifan, Li Xueshuang, Dong Jixian, Zheng Fang, Miao Yingliang, and Wang Zhifang. The previous versions of this document and the documents it replaces are as follows. ---First published in.2017 as GB/T 33767.1-2017; ---This is the first revision.introductionQuality metrics in biometrics are of great value. This document aims to provide a sample quality metric for the biometrics field. The quality score measurement framework defines the expression, interpretation and exchange methods of quality scores, providing an objective and This document is a quantitative basis for ISO /IEC 19794 (all parts), ISO /IEC 39794 (all parts) and ISO /IEC 19784-1. The standard provides specifications and guidance for the representation and exchange of quality block data of biometric samples. GB/T 33767 "Information Technology Biometric Sample Quality" is intended to consist of 15 parts. --- Part 1.Framework. The purpose is to establish biometric sample quality criteria, the expression, interpretation and exchange of quality metrics, and An evaluation method for quantitatively evaluating the performance of an algorithm. --- Part 4.Fingerprint image data. The purpose is to specify the definition and requirements of fingerprint image quality indicators, quality analysis methods and quality Measurement method. --- Part 5.Face image data. The purpose is to specify the definition and requirements of face image quality indicators, quality analysis methods and quality Measurement method. --- Part 6.Iris image data. The purpose is to specify the definition and quantitative calculation method of iris image quality indicators, iris image acquisition Set quality requirements and the coding format for quality data records. --- Part 7.Signature/Signature Time Series Data. The purpose is to specify the definition of signature/signature time series data quality indicators and Requirements, quality analysis methods and quality measurement methods. --- Part 8.Fingerprint skeleton data. The purpose is to specify the definition and requirements of fingerprint skeleton data quality indicators, quality analysis methods and Quality measurement methods. --- Part 9.Vascular image data. The purpose is to specify the definition and requirements of vascular image quality indicators, quality analysis methods and quality Measurement method. --- Part 10.Hand outline data. The purpose is to specify the definition and requirements of hand outline image quality indicators and quality analysis methods and quality measurement methods. --- Part 11.Signature/Dynamic data of signature processing. The purpose is to specify the quality index of the processed signature/dynamic data of signature Standard definition and requirements, quality analysis methods and quality measurement methods. --- Part 12.Facial feature data. The purpose is to specify the definition and requirements of facial feature data quality indicators and quality analysis methods and quality measurement methods. --- Part 13.Voiceprint data. The purpose is to specify the definition and requirements of voiceprint data quality indicators, quality analysis methods and quality standards. Measurement method. --- Part 14.DNA data. The purpose is to specify the definition and requirements of various DNA data quality indicators generated by high-throughput sequencing. quality requirements, quality analysis methods and quality measurement methods. --- Part 15.Palmprint image data. The purpose is to specify the definition and requirements of palmprint image data quality indicators and quality analysis methods and quality measurement methods. --- Part 16.Whole body image data. The purpose is to specify the definition and requirements of quality indicators of whole body image data and quality analysis methods and quality measurement methods. --- Part 17.Gait image sequence data. The purpose is to specify the definition and requirements of gait image sequence data quality indicators, quality Analytical methods and quality measurement methods. This document also establishes an evaluation framework designed to facilitate the use of scoring tools that can not only encourage technological innovation but also Helps to enhance the overall effectiveness of the biometric recognition system. Although the quality assessment and scoring tools proposed in GB/T 33767 are usually optional This flexibility ensures the broad applicability of the standard while allowing for specific Appropriately perform the different biometric modes specified in ISO /IEC 19794 (all parts) and ISO /IEC 39794 (all parts) Adjustment. This document emphasizes the connection between quality metrics and biometric samples, which is an important component of quality metric standardization. The quality fields specified in the chapter are incorporated into the biometric data exchange format, and the CBEFF (Common Biometric Exchange Format Framework) data The use of the header further enriches the expression of quality metrics, namely through CBEFF_BDB_quality (biometric data block quality) Represents a quality metric. The use of biometric sample quality metrics has many benefits. For example, providing real-time quality feedback during the enrollment phase can improve biometric In addition, quality metrics can also be combined with other samples or reference data during the comparison process to achieve data fusion. Through the application of this document, the biometric recognition system Designers and users of systems will be able to more effectively utilize quality metrics to analyze systems, identify potential problems, and discover Opportunities to improve performance. Information Technology Biometric Sample Quality Part 1.Framework1 ScopeThis document establishes the following for any or all biometric sample types as needed. a) terms and definitions used in the specification and use of quality metrics; b) purpose and interpretation of biometric quality scores; c) the impetus to develop datasets of biometric samples with the goal of standardizing quality scores; d) exchange formats for quality assessment algorithm results; e) Aggregation method of quality scores; f) Evaluation methods for the efficiency of quality assessment algorithms. This document does not include the following. a) specify minimum quality score requirements for samples, modules or systems; b) Standardization of quality assessment algorithms; c) Utility evaluation of biometric samples or references for manual inspection. This document applies to the expression, interpretation and exchange of biometric sample quality metrics, as well as the evaluation of the efficiency of quality assessment algorithms and the quality assessment process. The exchange of estimation method results provides guidance for the standardization of the quality of various biometric samples.2 Normative referencesThe contents of the following documents constitute the essential clauses of this document through normative references in this document. For referenced documents without a date, only the version corresponding to that date applies to this document; for referenced documents without a date, the latest version (including all amendments) applies to This document. Vocabulary-Part 37.Biometrics) Note. GB/T 5271.37-2021 Information technology vocabulary Part 37.Biometric identification (ISO /IEC 2382-37.2017, MOD) ISO /IEC 19785-2 Information technology — Common biometric exchange format framework — Part 2.Biometric registration machine istration authority) Note. GB/T 45284.1-2025 Information technology - Extensible biometric identification data exchange format - Part 1.Framework (ISO /IEC 39794-1. 2019, IDT)3 Terms and DefinitionsFor this document, the terms and definitions defined in ISO /IEC 2382-37, ISO /IEC 39794-1 and the following apply. The URLs for terminology databases used for standardization maintained by ISO and IEC are as follows. ......Tips & Frequently Asked Questions:Question 1: How long will the true-PDF of GB/T 33767.1-2025_English be delivered?Answer: Upon your order, we will start to translate GB/T 33767.1-2025_English as soon as possible, and keep you informed of the progress. The lead time is typically 3 ~ 5 working days. 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