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Performance of Gabor mean Feature Extraction Techniques for Ear Biometrics Recognition System

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
Bhanu Vadhwani, Vineet Khanna, Sandeep Kumar Gupta, Shubhlakshmi Agarwal
10.5120/ijca2017913797

Bhanu Vadhwani, Vineet Khanna, Sandeep Kumar Gupta and Shubhlakshmi Agarwal. Performance of Gabor mean Feature Extraction Techniques for Ear Biometrics Recognition System. International Journal of Computer Applications 168(12):1-2, June 2017. BibTeX

@article{10.5120/ijca2017913797,
	author = {Bhanu Vadhwani and Vineet Khanna and Sandeep Kumar Gupta and Shubhlakshmi Agarwal},
	title = {Performance of Gabor mean Feature Extraction Techniques for Ear Biometrics Recognition System},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2017},
	volume = {168},
	number = {12},
	month = {Jun},
	year = {2017},
	issn = {0975-8887},
	pages = {1-2},
	numpages = {2},
	url = {http://www.ijcaonline.org/archives/volume168/number12/27924-2017913797},
	doi = {10.5120/ijca2017913797},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Ear biometric recognition is used in a lot of applications as person identification in criminal cases, investigation, and security purpose. Feature optimization stage has an important role for accuracy of correct recognition. Gabor filter have a problem of high dimension and high redundancy. Sampling filter is a problem of not reducing features optimum way. In the proposed Gabor feature extraction technique the Gabor features are filtered using proposed mean filter and obtained optimum features for ear biometric dataset.

References

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Keywords

Ear Biometric Recognition, Gabor Filter, Analysis.