Automatic classification of acquisition problems affecting fingerprint images in automated border controls

Automated Border Control (ABC) systems are technologies designed to increase the speed and accuracy of the identity verifications performed at international borders. A great number of ABCs deployed in different countries use fingerprint recognition techniques because of their high accuracy and user acceptability. However, the accuracy of fingerprint recognition methods can drastically decrease in this application context due to user-sensor interaction factors. This paper presents two main contributions. The first of them consists in an experimental evaluation performed to search the main negative aspects that could affect the usability and accuracy in ABCs based on fingerprint biometrics. The mainly considered aspects consists in the presence of luggage and cleanness of the finger skin. The second contribution consists in a novel approach for automatically identifying the type of user-sensor interaction that caused quality degradations in fingerprint samples. This method uses a specific feature set and computational intelligence techniques to detect non-idealities in the acquisition process and to suggest corrective actions to travelers and border guards. To the best of our knowledge, this is the first method in the literature designed to detect problems in user-sensor interaction different from improper pressures on the acquisition surface. We validated the proposed approach using a dataset of 2880 images simulating different scenarios typical of ABCs. Results shown that the proposed approach is feasible and can obtain satisfactory performance, with a classification error of 0.098

The Application of the Human-Biometric Sensor Interaction Method to Automated Border Control Systems

Biometrics components are used in many different systems and technologies to verify that the user is whom they say they are. In Automated Border Control systems, biometrics components used in conjunction with a traveller's documents to make sure the user is whom they say they are so that they can cross into a countries borders. The systems are expected to verify the identity with a higher degree than officers who manually check travellers. Each year the number of travellers crossing through a country borders increases and so systems are expected to handle bigger demands; through improving the user experience to ensuring accuracy and performance standards increase. While the system does bring its benefits through increased speed and higher security, there are drawbacks. One of the main issues with the systems is a lack of standardisation across implementations. Passing through an automated process at Heathrow may be different to Hong Kong. The infrastructure, information, environment and guidance given during the transaction will all greatly differ for the user. Furthermore, the individual components and subsequent processing will be evaluated using a different methodology too. This thesis reports on the contrasts between implementations, looking at solutions which utilise different biometric modalities and travel documents. Several models are devised to establish a process map which can be applied to all systems. Investigating further, a framework is described for a novel assessment method to evaluate the performance of a system. An RGB-D sensor is implemented, to track and locate the user within an interactive environment. By doing so, the user's interaction is assessed in real-time. Studies then report on the effectiveness of the solution within a replicated border control scenario. Several relationships are studied to improve the technologies used within the scenario. Successful implementation of the automated assessment method may improve the user's experience with systems, improving information and guidance, increasing the likelihood of successful interaction while maintaining a high level of security and quicker processing times