The JAB Code, a 2D barcode standardized in ISO/IEC 23634:2022, offers improved reliability and data capacity over traditional barcodes, but its color recognition poses challenges. These issues stem from the suboptimal utilization of the RGB color space in printing and the non-bijective RGB-to-CMYK conversion, prompting the need to select colors that ensure distinct segregation in the transformed color space for enhanced detection robustness. We propose an approach for calibrating the colors of the JAB Code, involving the creation of a test pattern, quantization of the color space, and the calibration of colors using a calibration target. This method aims to ensure optimal color representation within the barcode and can be integrated into JAB Code generation tools or web apps, simplifying the process for users and ultimately improving color accuracy and fidelity within the barcode. We conduct an experiment with different printers, utilizing a smartphone for image capture. The evaluation includes printing JAB Code test patterns, creating and calibrating standard and calibrated JAB Codes, and capturing images under various lighting conditions. We use the JAB Code detection algorithm to analyze color distances in the RGB space, revealing improvements in color distribution and lower error rates with printer color calibration, which can lead to faster reading processes and smaller JAB Code sizes with reduced area requirements. This work offers important insights that should be considered during the next revision of the ISO standard.

During the pandemic the usage of video platforms skyrocketed among office workers and students and even today, when more and more events are held on-site again, the usage of video platforms is at an all-time high. However, the many advantages of these platforms cannot hide some problems. In the professional field, the publication of audio recordings without the consent of the author can get him into trouble. In education, another problem is bullying. The distance from the victim lowers the inhibition threshold for bullying, which means that platforms need tools to combat it. In this work, we present a system, which can not only identify the person leaking the footage, but also identify all other persons present in the footage. This system can be used in both described scenarios.

In this paper, we present a method to secure sovereign documents. It is based on technical guidelines from the International Civil Aviation Organization. A public key infrastructure is used to secure the document information. Therefore, the personal data of the sovereign document are used such as metadata and facial image. The data is digitally signed and stored in a JAB Code, a polychrome barcode, and printed on the sovereign document. With this procedure, security papers can be completely omitted for sovereign documents and the verification of integrity and authenticity can be done by any citizen using his smartphone. The evaluation of the implementation was performed on a generalized concept for sovereign documents together with the German Federal Office for Information Security.

This work discusses document security, use of OCR, and integrity verification related to printed documents. Since the underlying applications are usually documents containing sensitive personal data, a solution that does not require the entire data to be stored in a database is the most compatible. In order to allow verification to be performed by anyone, it is necessary that all the data required for this is contained on the document itself. The approach must be able to cope with different layouts so that the layout does not have to be adapted for each document. In the following, we present a concept and its implementation that allows every smartphone user to verify the authenticity and integrity of a document.

Identifying cultural assets is a challenging task which requires specific expertise. In this paper, a deep learning based solution to identify archaeological objects is proposed. Several additions to the ResNet CNN architecture are introduced which consolidate features from different intermediate layers by applying global pooling operations. Unlike general object recognition, identifying archaeological objects poses new challenges. To meet the special requirements in classifying antiques, a hybrid network architecture is used to learn the characteristics of objects using transfer learning, which includes a classification network and a regression network. With the help of the regression network, the age of objects can be predicted, which improves the overall performance in comparison to manually classifying the age of objects. The proposed scheme is evaluated using a public database of cultural assets and the experimental results demonstrate its significant performance in identifying antique objects.

In this paper, we present a development for recognizing objects from looted excavations. Experts with an archaeological background are not always available where an object needs to be assessed for tradability. For this purpose, we developed a smartphone app that can provide on-site assistance in the initial assessment of archaeological objects. The app sends captured images to a server for recognition and receives results with similar objects and their metadata along with an associated probability. A user can thus use these information to infer the provenance of the photographed object. To this end, a classifier was trained using a transfer learning procedure and the features of the trained network were used for an image matching procedure. The developed application will be tested by law enforcement agencies with a total of 15 smartphones for six months starting in early October.

This work shows a fingerprint method for the unique identification of blank and printed paper by a smartphone. This allows a secure authentication by authorities or end users of products or documents. The digital file includes no hidden data. The fingerprint method uses uncontrollable printing variabilities and paper structure as features. The uncontrollable variabilities are mapped into a binary sequnce, which is used as representation of the features and acts as our fingerprint. The variabilities can be extracted from low and high quality paper as well as from printed material created with low-cost office printers and high-end offset printing machines. Based on this fingerprint, various applications can be realized where the distinction between original and copy or forgery is essential, such as piracy of packaging, tickets, coupons or official documents. From the results of the evaluation it can be concluded that the proposed method is independent of the smartphones used, the paper, the printing technology and the color temperature of the ambient light. Furthermore, the test results show that the proposed method works robustly at different distances, from the smartphone camera to the paper.

This paper presents the design and implementation of an encoder and decoder of a colored barcode with high data density and storage capacity and freedom in shape. The approximately three times higher data density compared to conventional 2D matrix codes such as DataMatrix, QR or Aztec code is achieved by the use of eight colors and enables new applications, especially in the endconsumer market as well as in IT security. The challenges associated with the use of the color channel in printing with conventional office printers and recording by smartdevices under typical scenarios are addressed. The flexibility in the barcode shape is achieved by combining a primary and several secondary symbols according to a given scheme and give the necessary freedom for various applications. The presented code stores colors redundantly in a color palette as a reference in order to provide high robustness. JAB code, Just Another Barcode, has been specified, implemented, tested and is avaiable in github and www.jabcode.org under the license LGPL 2.1. JAB code is currently in the standardization process at the International Organization for Standardization ISO.

The majority of important documents continues to be issued as paper-based documents. The security of such documents still relies on increasing the cost of forgery by using special equipment for producing particular features on the document. Cryptographic digital signatures would allow for the production of more secure physical documents without using any special equipment. Hence we elaborate all requirements and a specific realization for securing physical documents based on digital signatures. One crucial question is how to store the digital signature and all auxiliary data on paper. We use JAB Code, a high-capacity matrix code, for this purpose. Our solution notably supports offline verification and satisfies long-term verifiability. A relaxed specification is defined for short-term verification. Finally, we demonstrate our solution for a birth certificate and for a short-dated medical prescription.

Partial or selective encryption is a well-known concept in multimedia security. It aims to achieve a level of security of multimedia encryption comparable to common encryption by encrypting only a relevant subset of the complete stream or file. The prime benefit of partial encryption is better performance due to fewer encryption operations. In addition, partially encrypted media data can often be parsed as well as unencrypted media if no header data is encrypted. The focus of partial encryption evaluation has almost always been the level of security that can be achieved. In this work, we discuss another aspect: when partial encryption of MP3 files is used in a DRM scenario, how many resources can be saved by it? As DRM usually is attacked by key sniffing or analogue recording, the security of the encryption itself is of lesser importance as long as it provides a sufficient hindrance to access the media data.

Data transmission over an inaudible audio channel describes a low-bandwidth alternative to exchange data between devices without any additional infrastructure. However, the established communication channel can be eavesdropped and manipulated by an attacker. To prevent this, we introduce a tailored protocol with smallest possible overhead to secure the communication. The proposed protocol produces an overhead of 256 bits for the handshake message for setting up the first conversation with each partner. Further, the protocol produces [msg_len/64] * 3 + 67 bits overhead for each message. The overhead of 67 bits at the beginning of each message corresponds to one second transmission time with the used FSK modulation in the frequency range of 16kHz-20kHz. The additional overhead of 3-bit per 64-bit sequence poses a relation of 95% message to 5% overhead. For the implementation of the protocol, algorithms implemented in the Crypto++ library such as SHA-256, CCM and PBKDF2 have been used.

To estimate the quality of a media operation, various metrics for the different media types are available. Although there are metrics that value the visual quality of operations on 3D data as well as on 2D data, there is no metric for the mapping of 2D data on 3D data, such as the mapping of texture images on 3D mesh models. In order to provide a metric that weighs the quality of textured 3D objects with respect on the human visual perception after the 2D and 3D data is watermarked independently, this work combines a mapping operation, a 2D metric and a 3D metric. The resulting approach allows measuring the visual impact of modifications of the texture as well as the 3D model on the final 3D object with all its textures mapped. Common application scenarios for that metric are video games, where 2D textures watermarked independent form the 3D model, but during the game play the textured 3D model is displayed.