finger vein is one of the most fitting biometric for identifying individuals. in this paper a new method for finger vein recognition is proposed. first the veins are extracted from finger vein images by using entropy based thresholding. in finger vein images the veins are appeared as dark lines. the method extracts veins as well, but the images are noisy, that means in addition to the veins the...

Neuronal microcircuits are formed of a myriad of spatially and functionally specific cell classes. Despite the importance of the spatial component in the characterisation of neural circuits, it has not received the attention it deserves. While multi-electrodes are widely used in the study of microcircuits, the spatial information available from them remains largely unexploited for analysis beyo...

Vertebrate photoreceptors are commonly distinguished based on the shape of their outer segments: those of cones taper, whereas the ones from rods do not. The functional advantages of cone taper, a common occurrence in vertebrate retinas, remain elusive. In this study, we investigate this topic using theoretical analyses aimed at revealing structure-function relationships in photoreceptors. Geom...

Searching for targets in large volume imagery is a challenging problem. A potentially promising solution, rapid image triage (RAIT), is essentially a cortically-coupled computer vision technique based on single-trial detection of event-related potentials (ERP). This paper presents a novel feature selection method, termed common spatio-temporal patterns (CSTP), which is critical for robust singl...

The common spatial pattern (CSP) algorithm is effective in decoding the spatial patterns of the corresponding neuronal activities from electroencephalogram (EEG) signal patterns in brain–computer interfaces (BCIs). However, its effectiveness depends on the subject-specific time segment relative to the visual cue and on the temporal frequency band that is often selected manually or heuristically...

The Alpha-Beta Log-Det divergences for positive definite matrices are flexible divergences that are parameterized by two real constants and are able to specialize several relevant classical cases like the squared Riemannian metric, the Steins loss, the S-divergence, etc. A novel classification criterion based on these divergences is optimized to address the problem of classification of the moto...

In this paper, we propose an improved filter selection method using Welch’s t-test based on discriminative filter bank common spatial pattern (DFBCSP). Existing DFBCSP used the Fisher ratio in order to find out discriminative filters. However, the Fisher ratio can be used to know only comparative value of distinguishability but may not become a meaningful criterion to reject null hypothesis. As...