EasyPASS - Evaluation of face recognition performance in 

an operational automated border control system 

Markus Nuppeney1 · Marco Breitenstein2 

1

Federal Office for Information Security (BSI) 

markus.nuppeney@bsi.bund.de 

2

secunet Security Networks AG 

marco.breitenstein@secunet.com 

1. Introduction 

The technical specifications [ICAO9303-1] [ICAO9303-2] for machine readable electronic 

passports (ePassports) have been approved by the International Civil Aviation Organization 

(ICAO) in 2006. More than 60 countries worldwide are meanwhile issuing ePassports 

according to the ICAO standards equipped with biometric facial images, which are stored in 

an embedded RF chip. With respect to border control processes, the usage of these ePassports 

generally allows for benefits regarding the following aspects: 

1. Improved security 

• electronic security mechanisms prevent forgery 

• biometrics prevent misuse of real documents by unauthorized persons 

2. Increased throughput 

• by using automated checking routines in classical control environments 

• by deploying automated border control systems, so-called eGates (electronic Gates) 

3. Ease of use 

• for the holder of the ePassport (self-service scenarios / eGates) 

• for the border control officer (more time for critical cases) 

Several countries have already implemented automated border control systems based on 

ePassports and facial recognition. Smartgate (Australia), RAPID (Portugal) and eBorders 

(United Kingdom) are currently the most prominent programs or projects in this area. 

Besides various operational aspects, there are also crucial technical questions to be considered 

regarding the biometric performance when introducing eGates and facial recognition at the 

borders: 

1. Is the quality of the ePassport images good enough to recognize people at an adequate 

level, i.e. are the images good enough to use them for automated facial recognition in 

a comfortable, reliable and secure manner? 

2. If so, is this true for the ePassports of all nations or just for a sub-set of countries 

spending high effort on quality assurance during the capture process of the facial 

images resp. photographs? 

To answer these questions the German government started the project EasyPASS to deploy an 

automated border control system at Frankfurt Airport based on facial recognition using the 

images from ePassports. 
Main characteristics and goals of the EasyPASS project are: 

• A balancing act between running face recognition systems in a real operational 

environment at the largest German airport and at the same time operating the systems 

in a way that allows well-founded biometric performance evaluation. 

• Performing an operational evaluation showing the performance as perceived by both 

passengers and border guards. 

• Performing a technical evaluation to be able to assess the biometric performance over 

the whole operating range. 

• Using several face recognition algorithms at the same time and under the same 

conditions to be able to compare their performance. 

• Using several quality assurance algorithms at the same time to evaluate the quality of 

the face images stored on the ePassports from the particular countries. 

• Operating the whole system in a secure way beside the biometric verification. That 

means complete checking of the documents’ optical and electronic security features as 

well as background checks. 

• Using the eGate systems in a self-service mode from the passengers’ point of view. 

• Possibility to cut off the evaluation functionality to convey the entire system to real 

operation mode (without extensive evaluation) when the evaluation phase of the 

project is over. 

2. EasyPASS system architecture 

In terms of hardware the EasyPASS system is characterized as follows (see Figures 1 and 2): 

• Each eGate comes with an entry and an exit door. 

• On the right side of the entry door each eGate is equipped with a full-page document 

reader to perform the optical ePassport checks and to read-out the electronic data from 

the chip. 

• To capture live images of the travellers, an intelligent self-adjusting camera system is 

embedded into the exit door of each eGate. 

Figure 1: EasyPASS system overview 
Figure 2: EasyPASS hardware setup - four operating eGates in parallel 

The entire software architecture of EasyPASS is based on the integration platform BioMiddle. 

BioMiddle facilitates the modular use of biometric system components and document readers 

within different biometric applications. Standardised interfaces allow for easy replacement of 

individual components. In particular, biometric hardware and software components are used 

as encapsulated Biometric Service Providers (BSP) and integrated via an integrated BioAPI 

2.0 framework according to the corresponding ISO/IEC standard [ISO19784-1]. The 

development of the BioMiddle framework was initiated in 2005 by the German Federal 

Office for Information Security (BSI) in order to be deployed in governmental biometric 

applications to guarantee modularity and exchangeability. 

An overview of the EasyPASS software architecture is shown below (see Figure 3). 

Figure 3: EasyPASS software architecture based on BioMiddle 
 

 

3. Project schedule 

The schedule of the project consists of three main phases: 

Phase 0 (Aug. – Sept. 2009): 

The system has been operated in “Biometric Data Collection Mode” in order to set up a 

database of facial images (passport-images and live-images) as the basis for performing the 

biometric performance evaluation. During “Phase 0” all participating passengers had to sign a 

declaration of consent regarding the storage of their facial images. 

Phase 1 (Oct. 2009 – March 2010): 

Since the beginning of October the system is running in “Evaluation Mode”, i.e. each passage 

of the EasyPASS eGates is logged in detail (timestamps, biometric quality characteristics, 

biometric scores etc.) but the personal and biometric data of the passengers is not stored in a 

database. From the passengers’ point of view the system operates like in “Regular Mode”. 

Phase 2 (from April 2010): 

At the change-over from “Evaluation Mode” to “Regular Mode” it is intended to cut off the 

evaluation functionality to convey the entire system to regular operation mode (without 

extensive evaluation). The parameterization of the system for “Phase 2” (biometric point of 

operation, employed biometric algorithm(s), etc.) depends on the evaluation results from 

“Phase 1”. 

4. Test setup and evaluation methodology 

The EasyPASS environment is equipped with extensive evaluation mechanisms. This covers 

mainly the following aspects: 

• Logging of events and results in particular to estimate rejection rates regarding 

o Face recognition (comparison scores instead of a simple decision) 

o Electronic security validation 

o Optical security validation 

o Background checks 

o Time measurements 

• Calculation of comparison scores with respect to 

o Multiple biometric algorithms (three different state-of-the-art face recognition 

algorithms are in use) 

o Calculation of comparison scores for genuines (live image of the passenger 

against the electronic ePassport image) 

o Calculation of comparison scores for simulated imposters (live image of the 

passenger against ePassports images of different persons stored in the 

evaluation database). 

This approach enables the calculation of all possible points of operation regarding 

FRR and FAR for each algorithm within in the real operational environment. 

• Performing quality measurements with respect to [ISO19794-5] of the ePassport 

images using multiple quality assurance algorithms (three different state-of-the-art 

algorithms are deployed within the system) 
All the biometric measurements and evaluations are performed online because of data 

protection considerations. The mentioned evaluations allow for a profound analysis of the 

system performance in sense of ROC curves, quality distributions, timing consideration etc. 

Based on these results the questions stated above can be addressed and answered in detail. 

5. Prospect 

The very first preliminary evaluation results are really promising. The EasyPASS system is 

operating in a manner that exceeds the expectations. This covers the performance shown by 

first analysis, the feedback of the border guards and above all the extremely positive feedback 

of the passengers. Established and detailed results will be available from April 2010 on, when 

the evaluation of the project (“Phase 1”) is finished. 

References 

[ICAO9303-1] ICAO Doc 9303, Machine Readable Travel Documents – Part1, Volume1: 

Passports with Machine Readable Data Stored in Optical Character 

Recognition Format, Sixth Edition, 2006. 

[ICAO9303-2] ICAO Doc 9303, Machine Readable Travel Documents – Part1, Volume2: 

Specifications for Electronically Enabled Passports with Biometric 

Identification Capability, Sixth Edition, 2006. 

[ISO19784-1] ISO/IEC 19784-1, Biometric application programming interface – Part1: 

BioAPI specification. 

[ISO19794-5] ISO/IEC 19794-5, Information technology – Biometric data interchange 

formats – Part5: Face image data.