Study of Biometric Identification Method Based on Naked Footprint

Raji Rafiu King, Wang Xiaopeng


DOI: https://doi.org/10.12777/ijse.5.2.29-35

Abstract


The scale of deployment of biometric identity-verification systems has recently seen an enormous increase owing to the need for more secure and reliable way of identifying people. Footprint identification which can be defined as the measurement of footprint features for recognizing the identity of a user has surfaced recently. This study is based on a biometric personal identification method using static footprint features viz. friction ridge / texture and foot shape / silhouette. To begin with, naked footprints of users are captured; images then undergo pre processing followed by the extraction of two features; shape using Gradient Vector Flow （GVF） snake model and minutiae extraction respectively. Matching is then effected based on these two features followed by a fusion of these two results for either a reject or accept decision. Our shape matching feature is based on cosine similarity while the texture one is based on miniature score matching. The results from our research establish that the naked footprint is a credible biometric feature as two barefoot impressions of an individual match perfectly while that of two different persons shows a great deal of dissimilarity.

Doi: 10.12777/ijse.5.2.29-35

How to cite this article: King, R.R. and Xiaopeng, W. (2013). Study of Biometric Identification Method Based on Naked Footprint . International Journal of Science and Engineering, 5(2),18-24. Doi: 10.12777/ijse.5.2.29-35]


Keywords


biometric; footprint; friction ridge; silhouette; verification

Full Text:

FULL TEXT PDF

References


. Ambeth, K. V. D. and Ramakrishnan M. (2010), Footprint recognition using modified sequential haar energy transform (MSHET), INTERNATIONAL JOURNAL OF COMPUTER SCIENCE ISSUES, (IJCSI) (7): 47

DOI: http://ijcsi.org/papers/7-3-5-47-51.pdf

. Ambeth, K. V. D. and Ramakrishnan M. (2012), Footprint recognition with cop using principle component analysis (PCA), JOURNAL OF COMPUTATIONAL INFORMATION SYSTEMS (8): 4939-4950.

DOI:http://www.jofcis.com/publishedpapers/2012_8_12_4939_4950.pdf

. Chenyang, X. and Prince, J. L. (1998), Generalized gradient vector flow external forces for active contours, SIGNAL PROCESSING, (71), 131-139.

DOI:http://iacl.ece.jhu.edu/~chenyang/research/pubs/spij98.pdf

. Hawes, M. R., Sovak, D., Miyashita, M., Kang, S. J., Yoshihuku, Y., Tanaka, S. (1994), Ethnic differences in forefoot shape and the determination of shoe comfort, ERGONOMICS, (37): 187.

DOI:http://www.tandfonline.com/doi/abs/10.1080/00140139408963637?journalCode=terg20

. Jung, J.W., Bien, Z., Lee S. W, Sato T., (2003), D Dynamic footprint based person Identification using mat-type pressure sensor, PROCEEDINGS OF THE 25TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE EMBS, Cancun Mexico, 2938–2940.

DOI:http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=01280533

. Marcialis G.L., Roli F., (2007), Score-level fusion of fingerprint and face matchers for personal verification under “stress” conditions, 14th INTERNATIONAL CONFERENCE ON IMAGE ANALYSIS AND PROCESSING, 259–264.

DOI:http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4362789

. Nakajima, K., Mizukami, Y., Tanaka, K., Tamura, T. (2000), Footprint based personal recognition, IEEE’S TRANSACTIONS ON BIOMEDICAL ENGINEERING, (47): 1534-1537.

DOI:http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=880106

. Tunkpien, P., Phimoltares, S., Panthuwadeethorn S., (2011), Palmprint identification system using shape matching and K-Nearest neighbour algorithm, INSTITUTE OF ELECTRICAL AND ELECTRONIC ENGINEER’S INTERNATIONAL CONFERENCE ON IMAGING SYSTEMS AND TECHNIQUES, IST 2011, 327–330,

DOI:http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5962227

. Ravi, J.K., Raja, B., Venugopal, K. R (2009), Fingerprint recognition using minutia score matching, INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE AND TECHNOLOGY. (1): 35-42,

DOI:http://arxiv.org/ftp/arxiv/papers/1001/1001.4186.pdf

. Ross A. A, Karthik N., Jain A. K, (2006), Handbook of multi biometrics, INTERNATIONAL SERIES ON BIOMETRICS, SPRINGER SCIENCE+BUSINESS MEDIA, LLC, 114 – 115 , ISBN-13: 978-0-387-22296-7

. Sébastien, M., Trusted biometrics under spoofing attacks ,TABULA RASA. DOI: http://www.tabularasa-euproject.org/

. Wei, J., Hai-Yang, C., Jie, G., Rong-Xiang, H., Ying-Ke, L., Xiao-Feng, W. (2012), Newborn footprint recognition using orientation feature, NEURAL COMPUTING AND APPLICATIONS, (21): 1855-1863.

DOI:http://link.springer.com/content/pdf/10.1007%2Fs00521-011-0530-9.pdf




Published by Department of Chemical Engineering University of Diponegoro Semarang
Google Scholar
IJSE  by http://ejournal.undip.ac.id/index.php/ijse is licensed under Creative Commons Attribution 3.0 License.