Recognition of Nonideal Iris Images Using Shape Guided Approach and Game Theory

Most state-of-the-art iris recognition algorithms claim to perform with a very high recognition accuracy in a strictly controlled environment. However, their recognition accuracies significantly decrease when the acquired images are affected by different noise factors including motion blur, camera diffusion, head movement, gaze direction, camera angle, reflections, contrast, luminosity, eyelid and eyelash occlusions, and problems due to contraction and dilation. The main objective of this thesis is to develop a nonideal iris recognition system by using active contour methods, Genetic Algorithms (GAs), shape guided model, Adaptive Asymmetrical Support Vector Machines (AASVMs) and Game Theory (GT). In this thesis, the proposed iris recognition method is divided into two phases: (1) cooperative iris recognition, and (2) noncooperative iris recognition. While most state-of-the-art iris recognition algorithms have focused on the preprocessing of iris images, recently, important new directions have been identified in iris biometrics research. These include optimal feature selection and iris pattern classification. In the first phase, we propose an iris recognition scheme based on GAs and asymmetrical SVMs. Instead of using the whole iris region, we elicit the iris information between the collarette and the pupil boundary to suppress the effects of eyelid and eyelash occlusions and to minimize the matching error. In the second phase, we process the nonideal iris images that are captured in unconstrained situations and those affected by several nonideal factors. The proposed noncooperative iris recognition method is further divided into three approaches. In the first approach of the second phase, we apply active contour-based curve evolution approaches to segment the inner/outer boundaries accurately from the nonideal iris images. The proposed active contour-based approaches show a reasonable performance when the iris/sclera boundary is separated by a blurred boundary. In the second approach, we describe a new iris segmentation scheme using GT to elicit iris/pupil boundary from a nonideal iris image. We apply a parallel game-theoretic decision making procedure by modifying Chakraborty and Duncan's algorithm to form a unified approach, which is robust to noise and poor localization and less affected by weak iris/sclera boundary. Finally, to further improve the segmentation performance, we propose a variational model to localize the iris region belonging to the given shape space using active contour method, a geometric shape prior and the Mumford-Shah functional. The verification and identification performance of the proposed scheme is validated using four challenging nonideal iris datasets, namely, the ICE 2005, the UBIRIS Version 1, the CASIA Version 3 Interval, and the WVU Nonideal, plus the non-homogeneous combined dataset. We have conducted several sets of experiments and finally, the proposed approach has achieved a Genuine Accept Rate (GAR) of 97.34% on the combined dataset at the fixed False Accept Rate (FAR) of 0.001% with an Equal Error Rate (EER) of 0.81%. The highest Correct Recognition Rate (CRR) obtained by the proposed iris recognition system is 97.39%

Robust iris recognition under unconstrained settings

Tese de mestrado integrado. Bioengenharia. Faculdade de Engenharia. Universidade do Porto. 201

Biometric iris image segmentation and feature extraction for iris recognition

PhD ThesisThe continued threat to security in our interconnected world today begs for urgent solution. Iris biometric like many other biometric systems provides an alternative solution to this lingering problem. Although, iris recognition have been extensively studied, it is nevertheless, not a fully solved problem which is the factor inhibiting its implementation in real world situations today. There exists three main problems facing the existing iris recognition systems: 1) lack of robustness of the algorithm to handle non-ideal iris images, 2) slow speed of the algorithm and 3) the applicability to the existing systems in real world situation. In this thesis, six novel approaches were derived and implemented to address these current limitation of existing iris recognition systems. A novel fast and accurate segmentation approach based on the combination of graph-cut optimization and active contour model is proposed to define the irregular boundaries of the iris in a hierarchical 2-level approach. In the first hierarchy, the approximate boundary of the pupil/iris is estimated using a method based on Hough’s transform for the pupil and adapted starburst algorithm for the iris. Subsequently, in the second hierarchy, the final irregular boundary of the pupil/iris is refined and segmented using graph-cut based active contour (GCBAC) model proposed in this work. The segmentation is performed in two levels, whereby the pupil is segmented first before the iris. In order to detect and eliminate noise and reflection artefacts which might introduce errors to the algorithm, a preprocessing technique based on adaptive weighted edge detection and high-pass filtering is used to detect reflections on the high intensity areas of the image while exemplar based image inpainting is used to eliminate the reflections. After the segmentation of the iris boundaries, a post-processing operation based on combination of block classification method and statistical prediction approach is used to detect any super-imposed occluding eyelashes/eyeshadows. The normalization of the iris image is achieved though the rubber sheet model. In the second stage, an approach based on construction of complex wavelet filters and rotation of the filters to the direction of the principal texture direction is used for the extraction of important iris information while a modified particle swam optimization (PSO) is used to select the most prominent iris features for iris encoding. Classification of the iriscode is performed using adaptive support vector machines (ASVM). Experimental results demonstrate that the proposed approach achieves accuracy of 98.99% and is computationally about 2 times faster than the best existing approach.Ebonyi State University and Education Task Fund, Nigeri

Economia di guerra

We process the unideal iris images that are acquired in an unconstrained situation and are affected severely by gaze deviations, eyelid and eyelash occlusions, non uniform intensities, motion blurs, reflections, etc. The proposed unideal iris recognition algorithm has two novelties as compared to the previous works; firstly, we propose to deploy a region-based active contour model to segment an unideal iris image with intensity inhomogeneity; Secondly, an iterative algorithm, called the Modified Contribution-Selection Algorithm (MCSA), is used in the context of coalitional game theory to select a subset of informative features without compromising the recognition rate. The verification performance of the proposed scheme is validated using the UBIRIS Version 1, the ICE 2005, and the WVU Unideal datasets. Index Terms — Iris recognition, region-based active contour model, coalitional game theory, modified contribution selection algorithm. 1

Cellulo: Tangible Haptic Swarm Robots for Learning

Robots are steadily becoming one of the significant 21st century learning technologies that aim to improve education within both formal and informal environments. Such robots, called Robots for Learning, have so far been utilized as constructionist tools or social agents that aided learning from distinct perspectives. This thesis presents a novel approach to Robots for Learning that aims to explore new added values by means of investigating uses for robots in educational scenarios beyond those that are commonly tackled: We develop a platform from scratch to be "as versatile as pen and paper", namely as composed of easy to use objects that feel like they belong in the learning ecosystem while being seamlessly usable across many activities that help teach a variety of subjects. Following this analogy, we design our platform as many low-cost, palm-sized tangible robots that operate on printed paper sheets, controlled by readily available mobile computers such as smartphones or tablets. From the learners' perspective, our robots are thus physical and manipulable points of hands-on interaction with learning activities where they play the role of both abstract and concrete objects that are otherwise not easily represented. We realize our novel platform in four incremental phases, each of which consists of a development stage and multiple subsequent validation stages. First, we develop accurately positioned tangibles, characterize their localization performance and test the learners' interaction with our tangibles in a playful activity. Second, we integrate mobility into our tangibles and make them full-blown robots, characterize their locomotion performance and test the emerging notion of moving vs. being moved in a learning activity. Third, we enable haptic feedback capability on our robots, measure their range of usability and test them within a complete lesson that highlights this newly developed affordance. Fourth, we develop the means of building swarms with our haptic-enabled tangible robots and test the final form of our platform in a lesson co-designed with a teacher. Our effort thus contains the participation of more than 370 child learners over the span of these phases, which leads to the initial insights into this novel Robots for Learning avenue. Besides its main contributions to education, this thesis further contributes to a range of research fields related to our technological developments, such as positioning systems, robotic mechanism design, haptic interfaces and swarm robotics

Students with Hidden Disabilities in Higher Education: Disruption, diffraction and the paradox of inclusion in theory and practice.

This thesis explores hidden disability and higher education through the perspective of New Materialisms and post-qualitative methodology: therefore, sitting within the Posthuman Disability Studies umbrella (Goodley et al, 2014). It questions and queries ableism and inclusion for disabled students in the marketised, neoliberal academy of the 21st Century. It argues that students with hidden disabilities are not offered an inclusive educational experience, but rather are assimilated into higher education’s ableistic practices. It also argues that inclusion, where this exists, happens as a singular event, with inclusion in one session and one moment being no guarantee of future moments of inclusion. It also argues that a complex range of multiple factors continually combine to create either inclusion or exclusion and that a simplistic, tick-box approach towards diversity ensures that inclusion of students with disabilities in higher education remains an aspiration, rather than a reality. Seven student-participants from one Post-92 university in the North-West of England contributed to this study. To explore inclusion and higher education, this thesis uses a range of entangled creative methods. Data utilised includes narrative interviews, poetry, photography, artwork and animation, these have been analysed through a diffractive methodological approach (Barad, 2014) which includes elements of speculative fiction, or ‘fabulations’ (Stewart, 2014). These fabulations are written in response to exclusionary educational events and offer mundane and everyday fictions of an inclusive future as-yet-to-come. Posthumanism has swiftly, and radically, shifted the boundaries of methodological research possibilities. This thesis responds to this boundary shift by drawing upon thinkers such as Braidotti (2012) and Deleuze and Guattari (1980/1987) to utilise transdisciplinary ‘minor’ rhizomatic writing to question ableistic and exclusionary knowledge production practices

Displaying fashion history: the linear, open, virtual, and absent museum

This doctoral project engages with historical and critical debates surrounding the presence of fashion exhibitions in the museum. In particular, it problematises the issue of the temporal distance between artefacts and audiences, presenting the idea that different ways of presenting fashion to audiences underlie different ways of constructing its history. It develops considerations on historiography and museology, supplementing the limiting distinction between historical, new historical and thematic exhibitions with a set of concepts that enable the discussion and the evaluation of the qualities of historical representations. It does so by taking as its case studies selected exhibition formats developed by the Victoria & Albert Museum (London), Museu Do Design e da Moda (Lisbon), Mode Museum (Antwerp), and Pitti Immagine & Fondazione Pitti Discovery (Florence). By observing the material features of their strategies of display, this research considers their ability to trigger interaction between visitors and content. In particular, it evaluates the ability of these strategies of display to shape visitors’ experiences by activating a gaze that has formed outside the museum, through the encounter with a broader culture of presentation. It sees the task of presenting the past through museum displays as grounded in practices of vision and modes of cognition in which experiences of temporality, narrative and modes of historical exploration surface as preformed and pre-individual. This project considers potential interchanges between critical museology, fundamental epistemological shifts in fashion theory, and curatorial discourse. At the same time, it opens interdisciplinary avenues for the study of the historiography of fashion, its relation to exhibition-making and to the visual and material culture in which museums are immersed. In doing so, its considerations account for aspects of existence that modern historiography has neglected: our bodily and spatial relationship with the world and with objects. In turn, the analysis develops considerations of the museum itself, utilising the chapters of the thesis also to build on the literature that has portrayed it as an institution invested in addressing conditions of cultural and temporal distance between artefacts and visitors. And thus, while on the one hand, the museum emerges as a strategic site for rethinking the history of fashion and its representations, on the other, presentations of fashion in the museum are seen as privileged contexts for the realisation of a contemporary form of museology: a practice which enacts processes of knowledge production through complex historical layering, negotiation with the world outside its premises, and the constant redefinition of canons

Properties and Applications of Graphene and Its Derivatives

Graphene is a two-dimensional, one-atom-thick material made entirely of carbon atoms, arranged in a honeycomb lattice. Because of its distinctive mechanical (e.g., high strength and flexibility) and electronic (great electrical and thermal conductivities) properties, graphene is an ideal candidate in myriad applications. Thus, it has just begun to be engineered in electronics, photonics, biomedicine, and polymer-based composites, to name a few. The broad family of graphene nanomaterials (including graphene nanoplatelets, graphene oxide, graphene quantum dots, and many more) go beyond and aim higher than mere single-layer (‘pristine’) graphene, and thus, their potential has sparked the current Special Issue. In it, 18 contributions (comprising 14 research articles and 4 reviews) have portrayed probably the most interesting lines as regards future and tangible uses of graphene derivatives. Ultimately, understanding the properties of the graphene family of nanomaterials is crucial for developing advanced applications to solve important challenges in critical areas such as energy and health