Robust Finger-vein ROI Localization Based on the 3σ Criterion Dynamic Threshold Strategy

Region of interest (ROI) localization is one of the key preprocessing technologies for a finger-vein identification system, so an effective ROI definition can improve the matching accuracy. However, due to the impact of uneven illumination, equipment noise, as well as the distortion of finger position, etc., these make accurate ROI localization a very difficult task. To address these issues, in this paper, we propose a robust finger-vein ROI localization method, which is based on the 3 σ criterion dynamic threshold strategy. The proposed method includes three main steps: First, the Kirsch edge detector is introduced to detect the horizontal-like edges in the acquired finger-vein image. Then, the obtained edge gradient image is divided into four parts: upper-left, upper-right, lower-left, and lower-right. For each part of the image, the three-level dynamic threshold, which is based on the 3 σ criterion of the normal distribution, is imposed to obtain more distinct and complete edge information. Finally, through labeling the longest connected component at the same horizontal line, two reliable finger boundaries, which represent the upper and lower boundaries, respectively, are defined, and the ROI is localized in the region between these two boundaries. Extensive experiments are carried out on four different finger-vein image datasets, including three publicly available datasets and one of our newly developed finger-vein datasets with 37,080 finger-vein samples and 1030 individuals. The experimental results indicate that our proposed method has very competitive ROI localization performance, as well as satisfactory matching results on different datasets.

Wind Data Anomaly Detection and Interpolation of Missing Data

Data accuracy and completeness of the wind farm has great significance in wind power research. Because of the wind farm in the process of gathering data and transmission appears distorted and missing, and that leads the accuracy and integrity of data is greatly reduced, so the need for a wind farm data, outlier detection and missing data imputation. This paper outlier detection by statistical method based on 3σ criterion under the normal distribution, and use of the effectiveness of the recently distance interpolation and regression interpolation for missing data, outliers and replacement and interpolation, filled after data and accuracy are improved.

Convection and 6Li in the atmospheres of metal-poor halo stars

Based on 3D hydrodynamical model atmospheres computed with the CO5BOLD code and 3D non-LTE (NLTE) line formation calculations, we study the effect of the convection-induced line asymmetry on the derived 6Li abundance for a range in effective temperature, gravity, and metallicity covering the stars of the Asplund et al. (2006) sample. When the asymmetry effect is taken into account for this sample of stars, the resulting 6Li/7Li ratios are reduced by about 1.5% on average with respect to the isotopic ratios determined by Asplund et al. (2006). This purely theoretical correction diminishes the number of significant 6Li detections from 9 to 4 (2σ criterion), or from 5 to 2 (3σ criterion). In view of this result the existence of a 6Li plateau appears questionable. A careful reanalysis of individual objects by fitting the observed lithium 6707 Å doublet both with 3D NLTE and 1D LTE synthetic line profiles confirms that the inferred 6Li abundance is systematically lower when using 3D NLTE instead of 1D LTE line fitting. Nevertheless, halo stars with unquestionable 6Li detection do exist even if analyzed in 3D-NLTE, the most prominent example being HD 84937.