Development of Vein Pattern in Leaves of Ostrya virginiana (Betulaceae)

1979 ◽  
Vol 140 (1) ◽  
pp. 77-83 ◽  
Author(s):  
Daniel H. Franck
Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1885
Author(s):  
Qiong Yao ◽  
Dan Song ◽  
Xiang Xu ◽  
Kun Zou

Finger vein (FV) biometrics is one of the most promising individual recognition traits, which has the capabilities of uniqueness, anti-forgery, and bio-assay, etc. However, due to the restricts of imaging environments, the acquired FV images are easily degraded to low-contrast, blur, as well as serious noise disturbance. Therefore, how to extract more efficient and robust features from these low-quality FV images, remains to be addressed. In this paper, a novel feature extraction method of FV images is presented, which combines curvature and radon-like features (RLF). First, an enhanced vein pattern image is obtained by calculating the mean curvature of each pixel in the original FV image. Then, a specific implementation of RLF is developed and performed on the previously obtained vein pattern image, which can effectively aggregate the dispersed spatial information around the vein structures, thus highlight vein patterns and suppress spurious non-boundary responses and noises. Finally, a smoother vein structure image is obtained for subsequent matching and verification. Compared with the existing curvature-based recognition methods, the proposed method can not only preserve the inherent vein patterns, but also eliminate most of the pseudo vein information, so as to restore more smoothing and genuine vein structure information. In order to assess the performance of our proposed RLF-based method, we conducted comprehensive experiments on three public FV databases and a self-built FV database (which contains 37,080 samples that derived from 1030 individuals). The experimental results denoted that RLF-based feature extraction method can obtain more complete and continuous vein patterns, as well as better recognition accuracy.


2013 ◽  
Vol 333-335 ◽  
pp. 1106-1109
Author(s):  
Wei Wu

Palm vein pattern recognition is one of the newest biometric techniques researched today. This paper proposes project the palm vein image matrix based on independent component analysis directly, then calculates the Euclidean distance of the projection matrix, seeks the nearest distance for classification. The experiment has been done in a self-build palm vein database. Experimental results show that the algorithm of independent component analysis is suitable for palm vein recognition and the recognition performance is practical.


2017 ◽  
pp. 5
Author(s):  
Alejandra Quintanar ◽  
Carmen de la Paz Pérez-Olvera ◽  
Isabel De la Cruz-Laina ◽  
Daría Razo-Balcazar

Wood anatomy of Alnus acuminata Kunth, Ostrya virginiana Rose, Quercus dyseophylla Benth. and Quercus glabrescens Benth., Arbutus glandulosa DC., Arbutus tessellata Sorensen, Styrax argenteus Presl. and Buddleia wrightii Robinson, collected in the state of Jalisco and Puebla are given. For each studied taxa, distinctive anatomical features are rebounded, and for each microscopic characteristic, photographs are given. Recommendations on their uses are suggested.


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