An Efficient Fingerprint Identification using Neural Network and BAT Algorithm

The uniqueness, firmness, public recognition, and its minimum risk of intrusion made fingerprint is an expansively used personal authentication metrics. Fingerprint technology is a biometric technique used to distinguish persons based on their physical traits. Fingerprint based authentication schemes are becoming increasingly common and usage of these in fingerprint security schemes, made an objective to the attackers. The repute of the fingerprint image controls the sturdiness of a fingerprint authentication system. We intend for an effective method for fingerprint classification with the help of soft computing methods. The proposed classification scheme is classified into three phases. The first phase is preprocessing in which the fingerprint images are enhanced by employing median filters. After noise removal histogram equalization is achieved for augmenting the images. The second stage is the feature Extraction phase in which numerous image features such as Area, SURF, holo entropy, and SIFT features are extracted. The final phase is classification using hybrid Neural for classification of fingerprint as fake or original. The neural network is unified with BAT algorithm for optimizing the weight factor

Biometric Systems

Because of the accelerating progress in biometrics research and the latest nation-state threats to security, this book's publication is not only timely but also much needed. This volume contains seventeen peer-reviewed chapters reporting the state of the art in biometrics research: security issues, signature verification, fingerprint identification, wrist vascular biometrics, ear detection, face detection and identification (including a new survey of face recognition), person re-identification, electrocardiogram (ECT) recognition, and several multi-modal systems. This book will be a valuable resource for graduate students, engineers, and researchers interested in understanding and investigating this important field of study

Fusion of face and iris biometrics in security verification systems.

Master of Science in Computer Science. University of KwaZulu-Natal, Durban, 2016.Abstract available in PDF file

Composing Music for Acoustic Instruments and Electronics Mediated Through the Application of Microsound

This project seeks to extend, through a portfolio of compositions, the use of microsound to mixed works incorporating acoustic instrument and electronics. Issues relating to the notation of microsound when used with acoustic instruments are explored and the adoption of a clear and intuitive system of graphical notation is proposed. The design of the performance environment for the electroacoustic part is discussed and different models for the control of the electronics are considered. Issues relating to structure and form when applied to compositions that mix note-based material with texture-based material are also considered. A framework based on a pure sound/noise continuum, used in conjunction with a hierarchy of gestural archetypes, is adopted as a possible solution to the challenges of structuring mixed compositions. Gestural and textural relationships between different parts of the compositions are also explored and the use of extended instrumental techniques to create continua between the acoustic and the electroacoustic is adopted. The role of aleatoric techniques and improvisation in both the acoustic and the electroacoustic parts are explored through adoption of an interactive performance environment incorporating a pitch-tracking algorithm. Finally, the advantages and disadvantages of real time recording and processing of the electronic part when compared with live processing of pre-existing sound-files are discussed

USSR Space Life Sciences Digest, issue 32

This is the thirty-second issue of NASA's USSR Space Life Sciences Digest. It contains abstracts of 34 journal or conference papers published in Russian and of 4 Soviet monographs. Selected abstracts are illustrated with figures and tables from the original. The abstracts in this issue have been identified as relevant to 18 areas of space biology and medicine. These areas include: adaptation, aviation medicine, biological rhythms, biospherics, cardiovascular and respiratory systems, developmental biology, exobiology, habitability and environmental effects, human performance, hematology, mathematical models, metabolism, microbiology, musculoskeletal system, neurophysiology, operational medicine, and reproductive system

Advances in Computer Recognition, Image Processing and Communications, Selected Papers from CORES 2021 and IP&C 2021

As almost all human activities have been moved online due to the pandemic, novel robust and efficient approaches and further research have been in higher demand in the field of computer science and telecommunication. Therefore, this (reprint) book contains 13 high-quality papers presenting advancements in theoretical and practical aspects of computer recognition, pattern recognition, image processing and machine learning (shallow and deep), including, in particular, novel implementations of these techniques in the areas of modern telecommunications and cybersecurity

Learning Robust Radio Frequency Fingerprints Using Deep Convolutional Neural Networks

Radio Frequency Fingerprinting (RFF) techniques, which attribute uniquely identifiable signal distortions to emitters via Machine Learning (ML) classifiers, are limited by fingerprint variability under different operational conditions. First, this work studied the effect of frequency channel for typical RFF techniques. Performance characterization using the multi-class Matthews Correlation Coefficient (MCC) revealed that using frequency channels other than those used to train the models leads to deterioration in MCC to under 0.05 (random guess), indicating that single-channel models are inadequate for realistic operation. Second, this work presented a novel way of studying fingerprint variability through Fingerprint Extraction through Distortion Reconstruction (FEDR), a neural network-based approach for quantifying signal distortions in a relative distortion latent space. Coupled with a Dense network, FEDR fingerprints were evaluated against common RFF techniques for up to 100 unseen classes, where FEDR achieved best performance with MCC ranging from 0.945 (5 classes) to 0.746 (100 classes), using 73% fewer training parameters than the next-best technique

Computer-Assisted Algorithms for Ultrasound Imaging Systems

Ultrasound imaging works on the principle of transmitting ultrasound waves into the body and reconstructs the images of internal organs based on the strength of the echoes. Ultrasound imaging is considered to be safer, economical and can image the organs in real-time, which makes it widely used diagnostic imaging modality in health-care. Ultrasound imaging covers the broad spectrum of medical diagnostics; these include diagnosis of kidney, liver, pancreas, fetal monitoring, etc. Currently, the diagnosis through ultrasound scanning is clinic-centered, and the patients who are in need of ultrasound scanning has to visit the hospitals for getting the diagnosis. The services of an ultrasound system are constrained to hospitals and did not translate to its potential in remote health-care and point-of-care diagnostics due to its high form factor, shortage of sonographers, low signal to noise ratio, high diagnostic subjectivity, etc. In this thesis, we address these issues with an objective of making ultrasound imaging more reliable to use in point-of-care and remote health-care applications. To achieve the goal, we propose (i) computer-assisted algorithms to improve diagnostic accuracy and assist semi-skilled persons in scanning, (ii) speckle suppression algorithms to improve the diagnostic quality of ultrasound image, (iii) a reliable telesonography framework to address the shortage of sonographers, and (iv) a programmable portable ultrasound scanner to operate in point-of-care and remote health-care applications

Sight, sound, the chicken and the egg: Audio-visual co-dependency in music

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Amongst the modern day abundance of audio-visual media, where sounds represent everything from the swooping of virtual cameras through 3D spaces to the pressing of buttons and receiving of emails, and conversely where VJs routinely accompany live musical performance with an increasingly sophisticated language of abstract computer animation, the notion of music as a necessarily exclusively aural medium seems somewhat out of place. Psychological theories relating to the cognition of sound, in particular physical schema, accounting for the ubiquity of vertical plane pitch metaphors in most musical cultures, provide evidence of a deep-rooted spatially informed understanding of sound thus providing a common ground for both sound and vision in music. Furthermore, Western Classical composition is rife with examples of visually conceived forms from Bach’s Crab Canon (1747) to Xenakis’ architecturally inspired Metastasis (1954). However, in practice the gap between the listener’s auditory experience and the composer’s visual concept is often insurmountable. Rising to Schaeffer’s call for “Primacy to the ear!” (Schaeffer, 1967, pp. 28-30), acousmatic composers have sought to derive music exclusively from experientially verifiable criteria. However, in its pervasiveness of other musical genres, no doubt aided by technologically and commercially driven domination of the pre-recorded over the live listening experience in the latter half of the twentieth century, such an approach has lead to the neglect of visual aspects in the live performance of much art-music. This research aims to begin to redress this balance through the composition of, largely computer realised, audio-visual works whose conception arises not from a superimposition of one medium upon another, but through the very relations between the media themselves. Utilising modern computers’ ability to synchronise physical and virtual visual events with synthesised sound in real time not only affords composers an invaluable tool for enhancing listener’s perception of formal structures but also implies causal relationships between the sonic and the visual which can provide a base of intuitive understanding on which more complex formal ideas can be built.Sponsored by the Brunel University Isambard Scholarship