Development of CUiris: A Dark-Skinned African Iris Dataset for Enhancement of Image Analysis and Robust Personal Recognition

Iris recognition algorithms, especially with the emergence of large-scale iris-based identification systems, must be tested for speed and accuracy and evaluated with a wide range of templates – large size, long-range, visible and different origins. This paper presents the acquisition of eye-iris images of dark-skinned subjects in Africa, a predominant case of verydark- brown iris images, under near-infrared illumination. The peculiarity of these iris images is highlighted from the histogram and normal probability distribution of their grayscale image entropy (GiE) values, in comparison to Asian and Caucasian iris images. The acquisition of eye-images for the African iris dataset is ongoing and will be made publiclyavailable as soon as it is sufficiently populated

A Survey on Ear Biometrics

Recognizing people by their ear has recently received significant attention in the literature. Several reasons account for this trend: first, ear recognition does not suffer from some problems associated with other non contact biometrics, such as face recognition; second, it is the most promising candidate for combination with the face in the context of multi-pose face recognition; and third, the ear can be used for human recognition in surveillance videos where the face may be occluded completely or in part. Further, the ear appears to degrade little with age. Even though, current ear detection and recognition systems have reached a certain level of maturity, their success is limited to controlled indoor conditions. In addition to variation in illumination, other open research problems include hair occlusion; earprint forensics; ear symmetry; ear classification; and ear individuality. This paper provides a detailed survey of research conducted in ear detection and recognition. It provides an up-to-date review of the existing literature revealing the current state-of-art for not only those who are working in this area but also for those who might exploit this new approach. Furthermore, it offers insights into some unsolved ear recognition problems as well as ear databases available for researchers

Measuring the Voice Resemblance Extent of Identical (Monozygotic) Twins Using Voiceprints Neutrosophic Domain

The identical twins (Monozygotic) are siblings created from the division of one fertilized egg (zygote), so they will be identical in their genetic characteristics and therefore in their phenotypic traits to a very large extent. Among these traits is the voice or the voiceprint of these twins. This research aims to suggest a method to determine the extent of the similarity and the difference between the voiceprints between the brothers of the identical twins and thus, it is possible to distinguish between their voices. This study relied on using a number of audio clips collected from 35 identical twins. The proposed method is based on the use of the spectrogram that represents the voiceprint of the twins. The spectrogram is a two-dimensional function that can be used in the Neutrosophic Transformation to convert the voiceprints to the Neutrosophic domain represented by three membership functions (True, False, and Indeterminate). The results showed that the average extent of the similarity ratio between twins’ voices (True membership) is 67.6%, the difference ratio (False membership) is 32.3%, and the indeterminacy membership function ratio is 18.2%

Infrared face recognition: a comprehensive review of methodologies and databases

Automatic face recognition is an area with immense practical potential which includes a wide range of commercial and law enforcement applications. Hence it is unsurprising that it continues to be one of the most active research areas of computer vision. Even after over three decades of intense research, the state-of-the-art in face recognition continues to improve, benefitting from advances in a range of different research fields such as image processing, pattern recognition, computer graphics, and physiology. Systems based on visible spectrum images, the most researched face recognition modality, have reached a significant level of maturity with some practical success. However, they continue to face challenges in the presence of illumination, pose and expression changes, as well as facial disguises, all of which can significantly decrease recognition accuracy. Amongst various approaches which have been proposed in an attempt to overcome these limitations, the use of infrared (IR) imaging has emerged as a particularly promising research direction. This paper presents a comprehensive and timely review of the literature on this subject. Our key contributions are: (i) a summary of the inherent properties of infrared imaging which makes this modality promising in the context of face recognition, (ii) a systematic review of the most influential approaches, with a focus on emerging common trends as well as key differences between alternative methodologies, (iii) a description of the main databases of infrared facial images available to the researcher, and lastly (iv) a discussion of the most promising avenues for future research.Comment: Pattern Recognition, 2014. arXiv admin note: substantial text overlap with arXiv:1306.160

VIRHUS: uma plataforma computacional para a simulação de sinais fisiológicos de humanos virtuais

The ability to access bio-signals of participants for research activity is limited specially for informal settings like academic projects. These limitations can be in part overcome it by using software to simulated good enough physiological data. In this work we propose and develop a computational platform to simulate (biological signals of ) virtual humans as a service. The system adopts the concept of digital twin to structure the simulation processes. In this case, the system is not sensing real participants, rather uses pre-recorded signals as inputs to auto-encoders that generate realistic synthetic signal for a virtual human, i.e., a digital twin. The pre-recorded signals used were the electrocardiogram, electrodermal activity and electromyography signals which were labeled with the ongoing emotion. The system, VIRHUS, offers an interactive web environment to create the required virtual humans and manage the simulation processes. A scalable backend takes care of the asynchronous generation of signals, that can be streamed to endpoints (and consumed by external applications) or exported as files, for convenience. As a proof of concept, the “virtual human” data can be parameterized to include emotional traits in the bio-signals (happy, sad,...), generating meaningful variations in data for applications developers.A capacidade de aceder aos biossinais de participantes para actividades de investigação é limitada, especialmente em contextos informais, tais como projectos académicos. Estas limitações podem ser parcialmente ultrapassadas através da utilização de software para simular dados fisiológicos suficientemente fidedignos. Neste trabalho, propomos e desenvolvemos uma plataforma computacional para simular (sinais biológicos de ) seres humanos virtuais como um serviço. O sistema adopta o conceito de réplica digital ("digital twin") para estruturar os processos de simulação. Neste caso, o sistema não está a monitorar participantes reais, mas utiliza sinais pré-gravados como entradas para autocodificadores que geram um sinal sintético realista para um ser humano virtual, ou seja, uma réplica digital. Os sinais pré-gravados utilizados foram o electrocardiograma, a actividade electrodérmica e os sinais electromiográficos que foram marcados com a emoção em progresso. O sistema, VIRHUS, fornece um ambiente web interactivo para criar os seres humanos virtuais necessários e gerir os processos de simulação. Um backend escalável cuida da geração assíncrona de sinais, que podem ser transmitidos para pontos de acesso programático (e consumidos por aplicações externas) ou exportados como ficheiros por conveniência. Como prova de conceito, os dados "humanos virtuais" podem ser parametrizados para incluir traços emocionais nos biossinais (feliz, triste,...), gerando variações significativas nos dados para os programadores de aplicações.Mestrado em Engenharia Informátic