I2I translation techniques for unpaired data are used for the creation of biometric presentation attack artefact samples. For the assessment of these synthetic samples, we analyse their behaviour when attacking hand vein recognition systems, comparing these results to such obtained from actually crafted presentation attack samples. We observe that although visual appearance and sample set correspondence are suprisingly good, respectively, the assessment of the behaviour of the data in a conducted attack is more difficult. Even if for some recognition schemes we find a good accordance in terms of IAPMR (for others we don't), the attack score distributions turn out to be highly dissimilar. More work is needed for reliable assesment of such data, to be able to correctly interpret corresponding results with respect to the usefulness in attack simulation.

For the first time, the feasibility of creating morphed samples for attacking vascular biometrics is investigated, in particular finger vein recognition schemes are addressed. A conducted vulnerability analysis reveals that (i) the extent of vulnerability, (ii) the type of most vulnerable recognition scheme, and (iii) the preferred way to determine the best morph sample for a given target sample depends on the employed sensor. Digital morphs represent a significant threat as vulnerability in terms of IAPMR is often found to be > 0.8 or > 0.6 (in sensor dependent manner). Physical artefacts created from these morphs lead to clearly lower vulnerability (with IAPMR ≤ 0.25), however, this has to be attributed to the low quality of the artefacts (and is expected be increase for better artefact quality).

Biometric system security requires cryptographic protection of sample data under certain circumstances. We assess low complexity selective encryption schemes applied to JPEG2000 compressed iris data by conducting iris recognition on the selectively encrypted data. This paper specifically compares the effects of a recently proposed approach, i.e. applying selective encryption to normalised texture data, to encrypting classical sample data. We assess achieved protection level as well as computational cost of the considered schemes, and particularly highlight the role of segmentation in obtaining surprising results.

We evaluate a set of general purpose bivariate image quality measures with respect to their ability to assess fingerprint-image quality. Our evaluation approach is able to identify specific weaknesses or strengths of quality indices with respect to certain types of quality impairments. To systematically generate corresponding test data, we apply StirMark image manipulations (as being developed in the context of watermarking robustness assessment) which are able to simulate a wide class of acquisition conditions and qualities, applicable to any given dataset and also of potential interest in forensic analysis. Experimental results document the competitiveness of the general purpose image quality measures in a comparison with dedicated univariate fingerprint-image quality measures.

A technique to generate non-invertible and revocable iris templates is proposed employing key-dependent wavelet transforms. In particular, parametrised wavelet-filters and wavelet packets are used in feature extraction in replacement of a pyramidal D4 wavelet transform. Since the template generation process is non-invertible by design, the overall scheme is non-invertible as well. Recognition accuracy is found to be high as long as personal tokens remain secret, templates can be revoked by simply exchanging the wavelet transform applied in the feature extraction process.

We propose to establish a standardised tool in fingerprint recognition robustness assessment, which is able to simulate a wide class of acquisition conditions, applicable to any given dataset and also of potential interest in forensic analysis. As an example, StirMark image manipulations (as being developed in the context of watermarking robustness assessment) are applied to fingerprint data to generate test data for robustness evaluations, thereby interpreting certain image manipulations as being highly related to realistic fingerprint acquisition conditions. Experimental results involving three different minutiae-based fingerprint matching schemes applied to FVC2004 data underline the need for standardised testing and a corresponding simulation toolset.

In wireless and mobile environments, universal media access is a key concept to facilitate efficient transmission of visual data by simple bitstream adaptation which relies on scalable coding schemes. Six different blind watermarking schemes are compared with respect to their watermark detection performance on scaled visual data. Specifically, resolution and quality scalability is considered in JPEG2000 and JPEG and the found watermark detection performance is related to the employed watermarking embedding strategies. It is found that in wireless environments, careful adjustment between watermark embedding and scalability modes is required to result in the desired watermark detection properties.

Distortion correction in two variants is applied to endoscopic duodenal imagery aiming at an improvement of automated classification of celiac disease affected mucosa patches. In a set of heterogeneous feature extraction techniques, only geometry and shape related ones are able to benefit from distortion correction, while for others, even a decrease of classification accuracy is observed. Different types of distortion correction do not lead to significantly different behaviour in the observed application scenario.

Privacy enhancing technologies in video surveillance are discussed for JPEG2000 codestreams. Protection accuracy, compression impact, and computational requirements are assessed and compared. Recommendations are given which approach is favourable under certain conditions.

To facilitate the embedding of fingerprinting payload corresponding to multiple re-sellings of a single image, multiple re-watermarking is a convenient technique. In this application context, oblivious detection techniques are important. Quantisation-based embedding technique are difficult to apply in this context without adapting them to the multiple watermarking scenario. We investigate two extensions to a wavelet coefficient-tree based embedding technique which turn out to improve detection performance in case of multiple re-watermarking.

Wavelet packets are shown to be a possible means to limit watermark interference in multiple re-watermarking algorithms. It turns out that when demanding a certain distance among wavelet packet subband trees, a significant improvement of watermark detection correlation values may be achieved in such a scenario.