Segmentation of slap fingerprints

This thesis describes a novel algorithm that segments the individual fingerprints in a multi-print image. The algorithm identifies the distal phalanx portion of each finger that appears in the image and labels them as an index, middle, little or ring finger. The accuracy of this algorithm is compared with the publicly-available reference implementation, NFSEG, part of the NIST Biometric Image Software (NBIS) suite developed at National Institute of Standards and Technology (NIST). The comparison is performed over large set of fingerprint images captured from unique individuals

Play Among Books

How does coding change the way we think about architecture? Miro Roman and his AI Alice_ch3n81 develop a playful scenario in which they propose coding as the new literacy of information. They convey knowledge in the form of a project model that links the fields of architecture and information through two interwoven narrative strands in an “infinite flow” of real books

The Assessment of Fingerprint Quality for a More Effective Match Score in Minutiae-Based Matching Performers

One of the most common types of evidence recovered from a crime scene are latent fingerprints, however these impressions are often of low quality. The quality of a latent fingerprint is described as the degree to which the ridge details can be observed. If the quality of the latent fingerprint is very clear, a minutiae-based matching algorithm with automatic extraction may detect and utilize the minutiae that are truly present in the fingerprint. However, if the impression is of poor quality, the minutiae-based matching algorithm\u27s automatic extraction may detect fewer features and could completely miss features resulting in the return of an unrelated candidate. The aim of this research was to determine a method to improve the match score of latent fingerprints by removing the bad quality regions, where both a subjective and objective methods were utilized. The subjective method utilized the predetermined quality categories of good, bad or ugly to assign a latent fingerprint. After classification, each impression was processed by AdobeRTM PhotoshopRTM and four quality areas were serially removed. In the objective method, each latent fingerprint was assessed with NFIQ algorithm and then MINDTCT algorithm. The MINDTCT algorithm provided a quality map that was used to remove successive portions of each latent fingerprint. The resulting new images from both methods were compared to a database using the two different minutiae-based matching algorithms: AFIX TrackerRTM and BOZORTH3.;The results were examined utilizing the statistical methods of receiver operator characteristic (ROC) curves, area under the ROC curve (AUC), cumulative match characteristic (CMC) curve, Wilcoxon signed-rank test, Spearman\u27s rank correlation and the comparison of the removal methods. ROC curves and the resulting AUC were able to determine that the AFIX TrackerRTM program is a reliable performer with high AUC values, while the BOZORTH3 minutiae-based algorithm did not perform well with low AUC scores of around 0.5. The results produced from the CMC curves showed that the subjective method produced higher rank 1 and top 10 rank identification than the objective method, contrary to what was hypothesized. The correlation scores showed the manual and automatic extraction were weakly correlated to one another. However, a very weak to no correlation between the algorithms of the BOZORTH3 and AFIX Tracker R was observed. The comparison between the subjective and objective methods of removal showed the examiner allowed for a more conservative removal of the fingerprint than the objective method. With this result in connection with the CMC curve results shows that being more conservative produces higher rank 1 and top ten rank identification scores

Play Among Books

How does coding change the way we think about architecture? Miro Roman and his AI Alice_ch3n81 develop a playful scenario in which they propose coding as the new literacy of information. They convey knowledge in the form of a project model that links the fields of architecture and information through two interwoven narrative strands in an “infinite flow” of real books

Security and Privacy for Modern Wireless Communication Systems

The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in node–edge–cloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks

Sonic interactions in virtual environments

This book tackles the design of 3D spatial interactions in an audio-centered and audio-first perspective, providing the fundamental notions related to the creation and evaluation of immersive sonic experiences. The key elements that enhance the sensation of place in a virtual environment (VE) are: Immersive audio: the computational aspects of the acoustical-space properties of Virutal Reality (VR) technologies Sonic interaction: the human-computer interplay through auditory feedback in VE VR systems: naturally support multimodal integration, impacting different application domains Sonic Interactions in Virtual Environments will feature state-of-the-art research on real-time auralization, sonic interaction design in VR, quality of the experience in multimodal scenarios, and applications. Contributors and editors include interdisciplinary experts from the fields of computer science, engineering, acoustics, psychology, design, humanities, and beyond. Their mission is to shape an emerging new field of study at the intersection of sonic interaction design and immersive media, embracing an archipelago of existing research spread in different audio communities and to increase among the VR communities, researchers, and practitioners, the awareness of the importance of sonic elements when designing immersive environments

Tune your brown clustering, please

Brown clustering, an unsupervised hierarchical clustering technique based on ngram mutual information, has proven useful in many NLP applications. However, most uses of Brown clustering employ the same default configuration; the appropriateness of this configuration has gone predominantly unexplored. Accordingly, we present information for practitioners on the behaviour of Brown clustering in order to assist hyper-parametre tuning, in the form of a theoretical model of Brown clustering utility. This model is then evaluated empirically in two sequence labelling tasks over two text types. We explore the dynamic between the input corpus size, chosen number of classes, and quality of the resulting clusters, which has an impact for any approach using Brown clustering. In every scenario that we examine, our results reveal that the values most commonly used for the clustering are sub-optimal