CFP last date
20 December 2024
Reseach Article

Application of Android-based Ear Biometrics Identification

by Ni Kadek Ayu Wirdiani, Ni Nyoman Triana Anggra Emi, A. A. K. Oka Sudana
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 172 - Number 10
Year of Publication: 2017
Authors: Ni Kadek Ayu Wirdiani, Ni Nyoman Triana Anggra Emi, A. A. K. Oka Sudana
10.5120/ijca2017915181

Ni Kadek Ayu Wirdiani, Ni Nyoman Triana Anggra Emi, A. A. K. Oka Sudana . Application of Android-based Ear Biometrics Identification. International Journal of Computer Applications. 172, 10 ( Aug 2017), 11-17. DOI=10.5120/ijca2017915181

@article{ 10.5120/ijca2017915181,
author = { Ni Kadek Ayu Wirdiani, Ni Nyoman Triana Anggra Emi, A. A. K. Oka Sudana },
title = { Application of Android-based Ear Biometrics Identification },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2017 },
volume = { 172 },
number = { 10 },
month = { Aug },
year = { 2017 },
issn = { 0975-8887 },
pages = { 11-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume172/number10/28286-2017915181/ },
doi = { 10.5120/ijca2017915181 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:19:58.473260+05:30
%A Ni Kadek Ayu Wirdiani
%A Ni Nyoman Triana Anggra Emi
%A A. A. K. Oka Sudana
%T Application of Android-based Ear Biometrics Identification
%J International Journal of Computer Applications
%@ 0975-8887
%V 172
%N 10
%P 11-17
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A biometrics-based security system is a security system that uses self-recognition technology using human body parts or behavior. This study uses the ear as a feature of biometrics. The image was taken or captured by using smartphone camera; the image was converted to grayscale and Gaussian Filter to reduce noise in the image. The extraction process done by three methods, they are: Canny Edge Detection, Hough Transform, and Oriented FAST and Rotated BRIEF (ORB). Canny Edge Detection is used to get the line in the ear, Hough Transform is used to look for ear circle shape. Invariant Moments to take the image value feature for both methods. ORB is used to search the ear keypoint, to get the feature value done by taking the ORB Feature. Identification process using Euclidean Distance for Canny Edge Detection and Hough Transform, meanwhile for ORB Method used Hamming Distance calculation. Combining these three methods resulted in a match rate of 54%.

References
  1. M. Lourde and D. Khosla, “Fingerprint Identification in Biometric SecuritySystems,” Int. J. Comput. Electr. Eng., vol. 2, no. 5, p. 852, 2010.
  2. D. Rusjayanthi, “Deviasi , dan K-Means Clustering,” vol. 4, no. 2, pp. 265–276, 2013.
  3. Darma Putra, Sistem Biometrika: Konsep Dasar, Teknik Analisis Citra, dan Tahapan Membangun Aplikasi Sistem Biometrika. Yogyakarta: Andi, 2009.
  4. I. N. Piarsa and R. Hisamuddin, “Sistem Verifikasi Online Menggunakan Biometrika Wajah,” vol. 9, no. 1, 2010.
  5. S. S. Mudholkar, P. M. Shende, and M. V Sarode, “Biometrics Authentication Technique for Intrusion Detection Systems Using Fingerprint Recognition,” Int. J. Comput. Sci. Eng. Inf. Technol., vol. 2, no. 1, pp. 57–65, 2012.
  6. N. B. Boodoo and R. K. Subramanian, “Robust multi-biometric recognition using face and ear images,” Int. J. Comput. Sci. Inf. Secur., vol. 6, no. 2, pp. 164–169, 2009.
  7. D. Suryadi, R. Hidayat, and H. A. Nugroho, “Pengembangan Sistem Identifikasi Multimodal Dengan Mengunakan Wajah Dan Telinga,” vol. 2014, no. Sentika, 2014.
  8. Ernastuti, “Implementasi Metode Hough Dan Jarak Mahalanobis Pada Sistem Biometrik Pengenalan Telinga Dengan Menggunakan Library Open CV,” 2012.
  9. S. Gunawan, Biologi untuk SMA/MA Kelas XI. Jakarta: Grasindo, 2007.
  10. Risky, Big Book Ilmu Pengetahuan Alam SD Kelas 4,5, & 6. Jakarta: Cmedia Imprint Kawan Pustaka, 2015.
  11. L. Widya, Buku Ajar Biologi Dasar dan Biologi Perkembangan (Kebidanan). Yogyakarta: Nuha Medika, 2015.
  12. M. Choraś, “Ear Biometrics Based on Geometrical Feature Extraction,” Electron. Lett. Comput. Vis. Image Anal., vol. 5, no. 3, pp. 84–95, 2005.
  13. Iannarelli, Ear Identification, Forensic I. California: Paramont Publishing Company, 1989.
  14. H. Yang, N. Zhang, Q. Zeng, Q. Yu, S. Ke, and X. Li, “HPLC Method for the Simultaneous Determination of Ten Annonaceous Acetogenins after Supercritical Fluid CO2 Extraction.,” Int. J. Biomed. Sci., vol. 6, no. 3, pp. 202–7, 2010.
  15. K. H. Pun and Y. S. Moon, “Recent advances in ear biometrics,” Proc.of Sixth IEEE Int’l Conf. Autom. Face GestureRecognition, pp. 164–169, 2004.
  16. J. Canny, A Computational Approach to Edge Detection. 1986.
  17. Darma Putra, Pengolahan Citra Digital. Yogyakarta: Andi, 2010.
  18. A. Mcandrew, “An Introduction to Digital Image Processing with Matlab Notes for SCM2511 Image Processing 1 Semester 1 , 2004,” 2004.
  19. E. Rublee, V. Rabaud, K. Konolige, and G. Bradski, “ORB: An efficient alternative to SIFT or SURF,” Proc. IEEE Int. Conf. Comput. Vis., no. November 2011, pp. 2564–2571, 2011.
  20. N. K. A. Wirdiani and A. A. K. Oka Sudana, “Medicinal plant recognition of leaf shape using Localized Arc Pattern Method,” Int. J. Eng. Technol., vol. 8, no. 4, pp. 1847–1854, 2016.
Index Terms

Computer Science
Information Sciences

Keywords

Ear Biometrics Canny Edge Detection Hough Transform Oriented FAST and Rotated BRIEF Euclidean Distance.