Improving hand vein recognition by score weighted fusion of wavelet-domain multi-radius local binary patterns

Among biometric modalities, hand vein patterns are seen as providing an attractive method for high-level security access applications owing to high impenetrability and good user convenience. For biometric recognition based on near-infrared dorsal hand vein images, Local Binary Patterns (LBP) have emerged as a highly effective descriptor of local image texture with high recognition performance reported. In this paper, the traditional approach with LBP applied in the spatial domain is extended to multi-radius LBP in the wavelet domain to provide a more comprehensive set of feature categories to capture grey-level variation characteristics of vein patterns, and score weighted fusion based on the relative discriminative power of each feature category is proposed to achieve higher recognition performance. The proposed methodology is shown to provide a more robust performance with a recognition rate in excess of 99% and an equal error rate significantly less than 2%

Insects

In this thematic series, engineers and scientists come together to address two interesting interdisciplinary questions in functional morphology and biomechanics: How do the structure and material determine the function of insect body parts? How can insects inspire engineering innovations

CAPILLARY CHANNEL POLYMER FIBER-BASED SCAFFOLDS FOR NEURAL REGENERATION

Over 50 million Americans are affected by ailments to the central nervous system (CNS) and it impacts the American economy over $400 billion a year. The number of people in the United States who have spinal cord injury (SCI) has been estimated to be approximately 276,000 persons as of 2014 with a range from 240,000 to 337,000 persons. The annual incidence of SCI, not including those who die at the scene of the accident is approximately 12,500 new cases each year. Due to the limited regenerative capacity of the adult CNS and lack of clinically effective therapies, these conditions commonly result in permanent functional deficits. SCI damages both ascending sensory and descending motor axonal pathways interrupting the transmission of synaptic signals between the brain and peripheral tissues. Although damaged axons attempt an initial regenerative response, this is rapidly aborted due to the presence of growth inhibitory molecules in CNS myelin and the glial scar and intrinsic limitations of adult CNS neuronal biochemistry such as the ability to maintain cAMP levels and upregulate the expression of `regeneration-associated genes\u27. On the other hand, TBI, stroke, and Parkinson\u27s disease result in neuronal cell death. The CNS has limited capacity to replace lost neurons because the neurons themselves are terminally differentiated and post-mitotic. Although neural stem cells (NSCs) have been identified in specialized regions of the adult brain such as the sub-ventricular zone (SVZ) and the sub-granular zones (SGZ), their number is insufficient and the pathological environment inadequate to support an effective regenerative response. The end goal of this project is to develop a biomimetic scaffold using grooved fibers for neural regeneration. This goal was met with a two-pronged approach. In the first approach, grooved fibers immobilized with bioactive adhesive molecule were developed to topographically guide regenerating axons. In the second approach, grooved fiber staples were used as cell-laden microcarriers and integrated into a composite hydrogel which demonstrated its ability to serve as a platform for cell proliferation. This latter approach can be translated into an injectable in situ crosslinkable scaffold that can be used for neural stem cell (NSC) delivery with the prospect of stem cell differentiation into neurons to replenish cell loss. The first part of this research focused on immobilizing a bioactive 140 kDa fragment of L1 neural cell adhesion molecule on uniquely designed groovy capillary channel polymer (CCP) fibers. L1-CAM is an attractive candidate for growth of spared axonal growth cones upon injury. It mediates CNS maturation, by means of neurite outgrowth, adhesion, fasciculation, migration, survival, myelination, axon guidance, synaptic plasticity and regeneration after trauma. High levels of L1 are expressed by growing axons during development and after SCI and there is a positive correlation between their expression and axonal growth. CCP fibers with surface immobilized L1-CAM were demonstrated to guide growth of primary neurons in vitro. In the latter part of this research, a methodology to fabricate CCP fiber staples was developed and these were employed as cell-laden microcarriers. These microcarriers were then integrated into a composite hydrogel blend and demonstrated high cell proliferation in vitro compared to control gels. This composite system can be a promising platform for NSC delivery and differentiation into neurons

Pattern Recognition

A wealth of advanced pattern recognition algorithms are emerging from the interdiscipline between technologies of effective visual features and the human-brain cognition process. Effective visual features are made possible through the rapid developments in appropriate sensor equipments, novel filter designs, and viable information processing architectures. While the understanding of human-brain cognition process broadens the way in which the computer can perform pattern recognition tasks. The present book is intended to collect representative researches around the globe focusing on low-level vision, filter design, features and image descriptors, data mining and analysis, and biologically inspired algorithms. The 27 chapters coved in this book disclose recent advances and new ideas in promoting the techniques, technology and applications of pattern recognition

Backwards is the way forward: feedback in the cortical hierarchy predicts the expected future

Clark offers a powerful description of the brain as a prediction machine, which offers progress on two distinct levels. First, on an abstract conceptual level, it provides a unifying framework for perception, action, and cognition (including subdivisions such as attention, expectation, and imagination). Second, hierarchical prediction offers progress on a concrete descriptive level for testing and constraining conceptual elements and mechanisms of predictive coding models (estimation of predictions, prediction errors, and internal models)

Visual Cortex

The neurosciences have experienced tremendous and wonderful progress in many areas, and the spectrum encompassing the neurosciences is expansive. Suffice it to mention a few classical fields: electrophysiology, genetics, physics, computer sciences, and more recently, social and marketing neurosciences. Of course, this large growth resulted in the production of many books. Perhaps the visual system and the visual cortex were in the vanguard because most animals do not produce their own light and offer thus the invaluable advantage of allowing investigators to conduct experiments in full control of the stimulus. In addition, the fascinating evolution of scientific techniques, the immense productivity of recent research, and the ensuing literature make it virtually impossible to publish in a single volume all worthwhile work accomplished throughout the scientific world. The days when a single individual, as Diderot, could undertake the production of an encyclopedia are gone forever. Indeed most approaches to studying the nervous system are valid and neuroscientists produce an almost astronomical number of interesting data accompanied by extremely worthy hypotheses which in turn generate new ventures in search of brain functions. Yet, it is fully justified to make an encore and to publish a book dedicated to visual cortex and beyond. Many reasons validate a book assembling chapters written by active researchers. Each has the opportunity to bind together data and explore original ideas whose fate will not fall into the hands of uncompromising reviewers of traditional journals. This book focuses on the cerebral cortex with a large emphasis on vision. Yet it offers the reader diverse approaches employed to investigate the brain, for instance, computer simulation, cellular responses, or rivalry between various targets and goal directed actions. This volume thus covers a large spectrum of research even though it is impossible to include all topics in the extremely diverse field of neurosciences

Towards building a more complex view of the lateral geniculate nucleus: Recent advances in understanding its role

The lateral geniculate nucleus (LGN) has often been treated in the past as a linear filter that adds little to retinal processing of visual inputs. Here we review anatomical, neurophysiological, brain imaging, and modeling studies that have in recent years built up a much more complex view of LGN . These include effects related to nonlinear dendritic processing, cortical feedback, synchrony and oscillations across LGN populations, as well as involvement of LGN in higher level cognitive processing. Although recent studies have provided valuable insights into early visual processing including the role of LGN, a unified model of LGN responses to real-world objects has not yet been developed. In the light of recent data, we suggest that the role of LGN deserves more careful consideration in developing models of high-level visual processing