Drop Fingerprint Recognition Method Based on Cluster Analysis and BP Neural Network

Qing Song; Dan Qing Du; Lu Yang; Gao Jie Meng; Xue Fei Mao

doi:10.4028/www.scientific.net/AMM.543-547.2099

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 543-547Drop Fingerprint Recognition Method Based on...

Drop Fingerprint Recognition Method Based on Cluster Analysis and BP Neural Network

Abstract:

The eigenvalues of some liquid drop fingerprints are of high similarity, which decreases the recognition accuracy rates of BP neural network. In order to solve this problem, recognition method based on cluster analysis and BP neural network is proposed in this paper. Cluster analysis is used to classify liquid samples according to the similarity of eigenvalues and narrow the recognition range for samples under study. The experimental results have proved that this method is able to increase the recognition accuracy rate from 83.42% to 99.83%.

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Periodical:

Applied Mechanics and Materials (Volumes 543-547)

Pages:

2099-2102

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.543-547.2099

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Online since:

March 2014

Authors:

Qing Song*, Dan Qing Du, Lu Yang, Gao Jie Meng, Xue Fei Mao

Keywords:

BP Neural Network (BPNN), Cluster Analysis, Liquid Drop Fingerprint

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* - Corresponding Author

References

[1] Song Qing. Research of the identification method based on Drop Analysis Technology and Droplet Fingerprint. Tianjin University (2005).

Google Scholar

[2] Qiu Zurong, Chen Xinhua, Li Xinghua. Fiber capacitance drop analyzer and its recognition algorithm, Journal of Tianjin University. Vol. 44 (2011), pp.445-449.

Google Scholar

[3] Hu Yingru. Recognition method of droplet. Shaanxi University of Science and Technology (2009).

Google Scholar

[4] Fei Mingjie. The design and research of portable fiber-capacitive drop analyzer. Tianjin University (2007).

Google Scholar

[5] Shi Zhongzhi. Neural Network. Higher Education Press (2009).

Google Scholar

[6] Yang Shuying. Matlab technology to realize pattern recognition and intelligent computing, version(2). Electronic Industry Press (2011).

Google Scholar