Improved Fingerprint Recognition Algorithm Application Study on Smart Home

Shu Qian Chen; Yang Lie Fu; Ming Yang Yin

doi:10.4028/www.scientific.net/AMR.734-737.2970

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 734-737Improved Fingerprint Recognition Algorithm...

Improved Fingerprint Recognition Algorithm Application Study on Smart Home

Abstract:

Study on a new type of fingerprint identification algorithm and its application in intelligent home electric control lock problem. The traditional fingerprint recognition algorithms on fingerprint minutiae matching accuracy is low, difficult to accurately extract details, leading to lock malfunction or could not be opened. In order to overcome this problem, improved Point pattern fingerprint recognition matching algorithm, joined the matching weight coefficient on the base of pattern matching algorithm, and gives the hardware structure of fingerprint identification system, the improved algorithm is successfully applied in smart home applications, the example shows that, the improved algorithm can effectively improve the recognition rate , reduce false positives, has a certain practical value.

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Periodical:

Advanced Materials Research (Volumes 734-737)

Pages:

2970-2973

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.734-737.2970

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Online since:

August 2013

Authors:

Shu Qian Chen, Yang Lie Fu, Ming Yang Yin

Keywords:

CC2530, Fingerprint Identification, Pattern Matching Algorithm, Smart Home

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References

[1] Xie Chunguang. ARM-based Automated Fingerprint Identification System Development. Microcomputer Information. Vol. 25 (2009), pp.292-294.

Google Scholar

[2] Chen Guojin. Fingerprint recognition safeguard based on ARM9. Mechanical & Electrical Engineering Magazine. Vol. 26 (2009), pp.46-50.

Google Scholar

[3] Memon N, Wong PW. A Buyer -Seller watermarking protocol. IEEE Trans. on Image Processing, Vol. 10(2007), pp.643-649.

DOI: 10.1109/83.913598

Google Scholar

[4] Bresson E, Catalano D, Pointcheval D. A simple public key cryptosystem with a double trapdoor decryption mechanism and itsapplications. In: Laih CS, ed. Aciacrypt 2003. LNCS 2894, Berlin, Springer-Verlag, (2003), P. 37-54.

DOI: 10.1007/978-3-540-40061-5_3

Google Scholar

[5] Wang Peng, ZhangYouguang. A Wave Matching Based Algorithm for Fingerprint Image Series Mosaicking. Journal of Computer-Aided Design & Computer Graphics. Vol. 21(2009), p.1467.

Google Scholar

[6] Maltoni D, Maio D. Handbook offingerprint recognition . New York: Springer, (2003).

Google Scholar

[7] Xu Lihua, Fan Yongsheng. Improved adaptive method for fingerprint image segmentation. Computer Engineering and Applications. Vol. 47, (2011), pp.161-163.

Google Scholar