Abstract-Classical iris biometric systems assume ideal environmental conditions and cooperative users for image acquisition. When conditions are less ideal or users are uncooperative or unaware of their biometrics being taken the image acquisition quality suffers. This makes it harder for iris localization and segmentation algorithms to properly segment the acquired image into iris and non-iris parts. Segmentation is a critical part in iris recognition systems, since errors in this initial stage are propagated to subsequent processing stages. Therefore, the performance of iris segmentation algorithms is paramount to the performance of the overall system. In order to properly evaluate and develop iris segmentation algorithm, especially under difficult conditions like off angle and significant occlusions or bad lighting, it is beneficial to directly assess the segmentation algorithm. Currently, when evaluating the performance of iris segmentation algorithms this is mostly done by utilizing the recognition rate, and consequently the overall performance of the biometric system. In order to streamline the development and assessment of iris segmentation algorithms with the dependence on the whole biometric system we have generated a iris segmentation ground truth database. We will show a method for evaluating iris segmentation performance base on this ground truth database and give examples of how to identify problematic cases in order to further analyse the segmentation algorithms.

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This work presents a novel dual-spectrum database containing both iris and periocular images synchronously captured from a distance and within a realistic indoor environment. This database was used in the 1 st Cross-Spectrum Iris/Periocular Recognition Competition (Cross-Eyed 2016). This competition aimed at recording recent advances in cross-spectrum iris and periocular recognition. Six submissions were evaluated for cross-spectrum periocular recognition, and three for iris recognition. The submitted algorithms are briefly introduced. Detailed results are reported in this paper, and comparison of the results is discussed.

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We investigate the potential of foot biometric features based on geometry, shape, and texture and present algorithms for a prototype rotation invariant verification system. An introduction to origins and fields of application for footprint-based personal recognition is accompanied by a comparison with traditional hand biometry systems. Image enhancement and feature extraction steps emphasizing specific characteristics of foot geometry and their permanence and distinctiveness properties, respectively, are discussed. Collectability and universality issues are considered as well. A visualization of various test results comparing discriminative power of foot shape and texture is given. The impact on real-world scenarios is pointed out, and a summary of results is presented.

a b s t r a c tAnti-spoofing is attracting growing interest in biometrics, considering the variety of fake materials and new means to attack biometric recognition systems. New unseen materials continuously challenge stateof-the-art spoofing detectors, suggesting for additional systematic approaches to target anti-spoofing. By incorporating liveness scores into the biometric fusion process, recognition accuracy can be enhanced, but traditional sum-rule based fusion algorithms are known to be highly sensitive to single spoofed instances. This paper investigates 1-median filtering as a spoofing-resistant generalised alternative to the sum-rule targeting the problem of partial multibiometric spoofing where m out of n biometric sources to be combined are attacked. Augmenting previous work, this paper investigates the dynamic detection and rejection of liveness-recognition pair outliers for spoofed samples in true multi-modal configuration with its inherent challenge of normalisation. As a further contribution, bootstrap aggregating (bagging) classifiers for fingerprint spoof-detection algorithm is presented. Experiments on the latest face video databases (Idiap Replay-Attack Database and CASIA Face Anti-Spoofing Database) and fingerprint spoofing database (Fingerprint Liveness Detection Competition 2013) illustrate the efficiency of proposed techniques.

This paper evaluates the development of prospects for cruising in Europe. It examines this within the broad framework of economic theory and maritime economics. Initially, the market structures and relationships applicable to cruising are considered with particular attention being paid to the linkages between the shipping markets and tourism and leisure. This conceptual analysis suggests that whilst cruising has a strong shipping element it does not fall exclusively within the classic framework of maritime economics but draws from both shipping and tourism and leisure. For reasons of clarity, a number of de® nitions are also provided covering maritime tourism and leisure, cruising, and supply and demand, as it relates to cruising. Following this, an overview of the cruise industry is included. This focuses primarily on the growth in the demand both world wide and at regional level. In particular, the analysis places the development of cruising in Europe in market perspective. Subsequently, the development of cruising in the UK is examined as a case study. Initially, UK market growth is analysed and it can be seen that the UK is now the second largest cruise market in the world after North America. Projections of the growth in UK demand to 2003 are also provided. The growth in supply is also studied and the UK targeted eet is identi® ed. In addition, the question of ownership is addressed. The prospects of employment for UK seafarers within the cruise industry are also considered and results obtained from the analysis suggest that it should be possible to increase the participation of UK and other European seafarers within the cruise industry at all levels and in all departments. In the ® nal section of the paper, the position of UK ports as terminals and destinations is evaluated. It is concluded that the fundamentals of the cruise business remain strong, and continued growth by the industry should be possible for the foreseeable future.

This work presents the 2 nd Cross-Spectrum Iris/Periocular Recognition Competition (CrossEyed2017). The main goal of the competition is to promote and evaluate advances in cross-spectrum iris and periocular recognition. This second edition registered an increase in the participation numbers ranging from academia to industry: five teams submitted twelve methods for the periocular task and five for the iris task. The benchmark dataset is an enlarged version of the dual-spectrum database containing both iris and periocular images synchronously captured from a distance and within a realistic indoor environment. The evaluation was performed on an undisclosed test-set. Methodology, tested algorithms, and obtained results are reported in this paper identifying the remaining challenges in path forward.