Nested Object Watermarking: From the Rectangular Constraint to Polygonal and Private Annotations

A specific application for image watermarking is constituted by annotation watermarking (sometimes also called caption or illustration watermarking). In this domain, supplementary information is embedded directly in the media, so that additional information is intrinsically linked to media content and does not get separated from the media by non-malicious processing steps such as image cropping or compression. Recently, nested object annotation watermarking (NOAWM) has been introduced as a specialization in annotation watermarking, whereby hierarchical object relations are embedded in photographic images. Earlier work has suggested two methods for achieving this, whereby two main deficits can be identified for those: firstly both methods perform approximation of the user-generated, free-hand, polygonal shape annotations to rectangular annotation areas, which leads to a significant loss in precision of the annotation region after detection. Secondly, both of the previous algorithms do not introduce any security mechanisms, i.e. the object annotations are publicly accessible with no access control mechanism. This paper presents an extension to one of the two previous approaches to suggest a first solution to these shortcomings. For this purpose, a novel method for embedding both the shape of the embedding region and the textual annotations in the phase coefficients of the Discrete-Fourier Transform (DFT) is presented. In order to achieve user dependent access control and improved synchronization for this scheme, the new method involves keydependency. The key is used to provide an application level security feature and it is not designed yet in the sense of watermark key-space or sub-space security. The suggested methods have been prototypically implemented and first experimental results are presented in comparison to the original method with respect to transparency and robustness. We show that our new scheme may significantly reduce the transparency in terms of Peak-Signal-to-Noise Ratio (PSNR), whereas the overall watermark detection rate decreases, mainly due to local synchronization limitations

Study of Applicability of Virtual Users in Evaluating Multimodal Biometrics

Abstract. A new approach of enlarging fused biometric databases is presented. Fusion strategies based upon matching score are applied on active biometrics verification scenarios. Consistent biometric data of two traits are used in test scenarios of handwriting and speaker verification. The fusion strategies are applied on multimodal biometrics of two different user types. The real users represent two biometric traits captured from one person. The virtual users are considered as the combination of two traits captured from two discrete users. These virtual users are implemented for database enlargement. In order to investigate the impact of these virtual users, test scenarios using three different semantics of handwriting and speech are accomplished. The results of fused handwriting and speech of exclusively real users and additional virtual users are compared and discussed

Benchmarking Quality-Dependent and Cost-Sensitive Score-Level Multimodal Biometric Fusion Algorithms

Automatically verifying the identity of a person by means of biometrics is an important application in day-to-day activities such as accessing banking services and security control in airports. To increase the system reliability, several biometric devices are often used. Such a combined system is known as a multimodal biometric system. This paper reports a benchmarking study carried out within the framework of the BioSecure DS2 (Access Control) evaluation campaign organized by the University of Surrey, involving face, fingerprint, and iris biometrics for person authentication, targeting the application of physical access control in a medium-size establishment with some 500 persons. While multimodal biometrics is a well-investigated subject, there exists no benchmark for a fusion algorithm comparison. Working towards this goal, we designed two sets of experiments: quality-dependent and cost-sensitive evaluation. The quality-dependent evaluation aims at assessing how well fusion algorithms can perform under changing quality of raw images principally due to change of devices. The cost-sensitive evaluation, on the other hand, investigates how well a fusion algorithm can perform given restricted computation and in the presence of software and hardware failures, resulting in errors such as failure-to-acquire and failure-to-match. Since multiple capturing devices are available, a fusion algorithm should be able to handle this nonideal but nevertheless realistic scenario. In both evaluations, each fusion algorithm is provided with scores from each biometric comparison subsystem as well as the quality measures of both template and query data. The response to the call of the campaign proved very encouraging, with the submission of 22 fusion systems. To the best of our knowledge, this is the first attempt to benchmark quality-based multimodal fusion algorithms

Pattern Recognition for IT Security, Book of Abstracts

This publication contains the abstracts of all papers which were presented during the workshop "Pattern Recognition for IT Security", held on September 21, 2010 in Darmstadt in conjunction with the 32nd Annual Symposium of the German Association for Pattern Recognition (DAGM 2010)

Image Annotation Watermarking: Nested Object Embedding using Hypergraph Model. MM&Sec 2006

In this paper, we introduce to the special domain of image annotation watermarking, based on embedding of hierarchical data related to objects into user-selected areas on an image. In comparison to earlier methods, the main goal of the work presented here is to provide a specific robustness, specifically against cropping, in a way that preserves hierarchical object relations even after retrieval from a partial image, which has been cut from the original (pure security aspects are of limited relevance for our application). We identify two initial categories for such relations, visual-functional and visual-spatial and suggest a novel coding scheme for the first of these. Our prototypical system consists of a new ontology-based interactive editor and a watermarking scheme, which is an extension of previously suggested block-based image watermarking towards the specific requirements for annotation watermarking. Our initial experiments of the new approach include evaluation of appropriate synchronization patterns and issues of their thresholdbased exhaustive search. Further, we present results from robustness tests, which are based on cropping and lossy JPEG compression. Our findings show that the suggested method is capable to restore payload in a hierarchy-preserving way after up to 50 % JPEG compression, with a low to medium loss of transparency, which has been evaluated subjectively. Further, we observe that even when limiting exhaustive search to those watermark candidates showing the highest embedding energy, we are able to correctly detect between 55 % and 100 % of cropped objects

Handwriting: Feature Correlation Analysis for Biometric Hashes

In the application domain of electronic commerce, biometric authentication can provide one possible solution for the key management problem. Besides server-based approaches, methods of deriving digital keys directly from biometric measures appear to be advantageous. In this paper, we analyze one of our recently published specific algorithms of this category based on behavioral biometrics of handwriting, the biometric hash. Our interest is to investigate to which degree each of the underlying feature parameters contributes to the overall intrapersonal stability and interpersonal value space. We will briefly discuss related work in feature evaluation and introduce a new methodology based on three components: the intrapersonal scatter (deviation), the interpersonal entropy, and the correlation between both measures. Evaluation of the technique is presented based on two data sets of different size. The method presented will allow determination of effects of parameterization of the biometric system, estimation of value space boundaries, and comparison with other feature selection approaches

Analyzing a multimodal biometric system using real and virtual users

Three main topics of recent research on multimodal biometric systems are addressed in this article: The lack of sufficiently large multimodal test data sets, the influence of cultural aspects and data protection issues of multimodal biometric data. In this contribution, different possibilities are presented to extend multimodal databases by generating so-called virtual users, which are created by combining single biometric modality data of different users. Comparative tests on databases containing real and virtual users based on a multimodal system using handwriting and speech are presented, to study to which degree the use of virtual multimodal databases allows conclusions with respect to recognition accuracy in comparison to real multimodal data. All tests have been carried out on databases created from donations from three different nationality groups. This allows to review the experimental results both in general and in context of cultural origin. The results show that in most cases the usage of virtual persons leads to lower accuracy than the usage of real users in terms of the measurement applied: the Equal Error Rate. Finally, this article will address the general question how the concept of virtual users may influence the data protection requirements for multimodal evaluation databases in the future