In this paper, we propose a novel cross-spectral matching system for identity verification based on the palm-vein and the palmprint acquired from the visible (RGB) and the near infrared (NIR) image spectral bands. Considering the vast availability of the visible library, the red and the blue spectrums are treated as sources of gallery samples and the NIR spectral band is utilized as the probe source without loss of generality. Apart from the extraction of palm-vein and palmprint features, the discriminative power of the palmprint templates is enhanced using a simplified Local Binary Pattern (LBP) encoding scheme. The similarity scores obtained by matching the NIR palm-vein templates against the registered RGB palm-vein templates is finally fused with scores obtained from matching the NIR palmprint codes against the registered RGB palmprint codes. Our empirical results on two publicly available multi-spectral palm databases show that the proposed system consistently achieves promising verification performance.
Although well-theorized causal explanations exist at the person level, scholars of environmental behavior have long neglected the social nature of environmental activism. Using a unique data set of individuals nested within local communities along the Han River, South Korea, we propose a novel empirical model for analyzing the contextual effect of social capital on different sets of self-reported environmental behaviors. Our findings, based on multilevel structural equation modeling, indicate that the community-level construct of social capital is a significant predictor of spatial variations in both private and public environmental behaviors, whereas the person-level construct of community ties has predictive power for private environmental behavior. Understanding these multilayered paths in which social capital relates to pro-environmental behaviors provides a crucial balance to previous single-level findings.
In this paper, we investigate into utilization of images from the visible light (RGB) spectrum for identity verification based on the palm-veins. This is differentiated from the commonly utilized Nearinfrared (NIR) images for palm-vein feature extraction. Our goal is to explore into the often omitted palm-vein information from the RGB palm images considering the vast deployment of the RGB cameras. Essentially, the vein line features are extracted at various scales based on an efficient difference image projection. The extracted features from the gallery and the probe images are matched based on a modified Hamming distance measure. The resultant similarity scores are finally fused at score level for accuracy enhancement. Experiments are conducted on two public multi-spectral palm databases. The results show encouraging matching accuracy and computational efficiency of the proposed method which extracts the palm-vein utilizing only the visible spectrum. The outcome of this study can be deployed as a standalone biometric or as part of a multibiometric system for secured authentication.
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