Design and Implementation of Smart E- Voting System Based on Finger Vein Recognition

Author
Joseph S, Roy Sudha Reetha P, Jenith J
Keywords
E-Voting; Finger-Vein; Support Vector Machine.
Abstract
Finger vein division is a significant issue in the unique mark acknowledgment framework. A finger vein picture must be sectioned to evacuate uninterested areas in different advances, for example, improvement and details identification with the goal of the picture handling will expend less CPU time. The picture of finger vein comprises various areas such as non-edge districts, top-notch edge locales, and low-quality edge areas. Finger vein identification is, as a rule, to recognize non-edge districts and unrecoverable low-quality edge areas and reject them as a foundation. Most division techniques are square wised which, partition the finger vein picture into un-covered squares and settle on the foundation and frontal area of each square. Some different strategies are pixel-wised ones which decide the sort of every pixel. Finger vein correction regularly registers the component (or highlight vector) of every component, square or pixel, and afterward decides the component’s sort dependent on the element (vector). The highlights utilized in finger vein division for the foremost part incorporate measurable highlights of pixel power, directional picture, and edge projection. The proposed Finger vein Identification and check System may be a biometric recognizable proof technique that utilizes computerized imaging innovation to accumulate, store, and investigate finger vein information. Here we are presenting another technique for finger vein ID innovation by utilizing SVM calculation.
References
[1] W. Zhong, X. Ning, and C. Wei, “A fingervein matching algorithm based on the relative topological relationship among minutiae,” in Proc. Int. Conf.NeuralNetw. Signal Process. Jun. 2008, pp. 225–228.
[2] E. Liu et al., “A key binding system based on n-nearest minutiae structure of fingervein,” Pattern Recognit. Lett., vol. 32, no. 5, pp. 666–675, Apr. 2011.
[3] R. Cappelli, M. Ferrara, and D. Maltoni, “Fingervein indexing based on minutia cylinder-code,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 5, pp. 1051–1057, Mar. 2011.
[4] F. Benhammadi, H. Hentous, K. Bey-Beghdad, and M. Aissani, “Fingervein matching using minutiae coordinate systems,” in Proc. PatternRecognit. Image Anal., 2005, pp. 9–19.
[5] X. Jiang and W. Y. Yau, “Fingervein minutiae matching based on the local and global structures,” in Proc. 15th ICPR, 2000, pp. 1038–1041.
[6] H. Ogawa, “Labeled point pattern matching by Delaunay triangulation and maximal cliques,” Pattern Recognit., vol. 19, no. 1, pp. 35–40, 1986.
[7] M. Abellanas, F. Hurtado, and P. A. Ramos, “Structural tolerance and Delaunay triangulation,” Inform. Process. Lett., vol. 71, nos. 5–6, pp. 221–227, Sep. 1999.
[8] A. A. Khanban and A. Edalat, “Computing Delaunay triangulation with imprecise input data,” in Proc. 15th Can. Conf. Comput. Geometry, 2003, pp. 94–97.
[9] G. Bebis, T. Deaconu, and M. Georgiopoulos, “Fingervein identification using Delaunay triangulation,” in Proc. Int. Conf. Inform. Intell. Syst., 1999, pp. 452.

Received : 28 August 2020
Accepted : 12 December 2020
Published : 07 January 2021
DOI: 10.30726/esij/v7.i4.2020.74024

Download “Design and Implementation of Smart E- Voting System Based on Finger Vein Recognition” 24.-Smart-E-Voting-System-based-on-Finger-Vein-Recognition.pdf – Downloaded 51 times – 173 KB