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Research on Retinal and Iris Identification Systems

Yıl 2017, Cilt: 2 Sayı: 1, 167 - 180, 25.02.2017

Öz

Biometrics is the science that
analyzes biological data and also the technology that measures biological data.
Biometric systems make identification or identity verification by using
measurable, distinctive physical and behavioral properties of humans. The most
widely used biometrics techniques rely on finger prints, palm, hand geometry,
iris, retina, face, ear shape, vein, signature, hand writing and voice
identification of an individual. Iris identification systems and retina
identification systems are the most accurate and reliable identifying
techniques. Iris is a circular structure surrounding the pupil, which determines
eye color. The iris is a very rich tissue and it has a unique texture. This
texture is different for each individual and it will stay same throughout their
lives. Iris identification systems use the mathematical pattern-identification
algorithms and statistical methods on individuals’ captured iris images.
Retina, similar to iris, is unique for each person and has an unchanging
texture throughout the life, except for some side effects of diseases. Retina
that is located in the back side of the eye is responsible for vision. The mesh
of blood vessels in retina is very complicated and distinctive. In retina
identification systems, firstly, infrared light is radiated into the eye and
blood vessels create unique reflections of this light. Retina identification is
used in many areas from security systems to medical applications. This study
examines and presents similarities and differences between two ocular biometric
systems which are iris identification systems and retina identification
systems. Analysis has also been carried out suing the findings of this study.

Kaynakça

  • [1]. Turhan C., Ceyhan, E., Sağıroğlu Ş., Biyometrik Sistemlerde Güvenlik Üzerine Bir İnceleme, www.iscturkey.org, access: 03.03.2016.
  • [2]. Yalçın, N., Gürbüz, F., 2015. Biyometrik Güvenlik Sistemlerinin İncelenmesi, Düzce Üniversitesi Bilim ve Teknoloji Dergisi, cilt 3, no. 2, pp.
  • [3]. Elumalai, K., Kannan, M., 2011. Multimodal Authentication For High End Security, International Journal on Computer Science and Engineering (IJCSE), 3(2), 687-692.
  • [4]. Jain, K., Bolle, R., Pankanti, S., 1999. Biometrics: Personal identification in Networked Society, Springer Science and Business Media.
  • [5]. Ergen, B., Çalışkan, A., 2011. Biyometrik Sistemler ve El Tabanlı Biyometrik Tanıma Karakteristikleri, 6th International Advanced Technologies Symposium, Elazığ-Türkiye.
  • [6]. Jain, A.K., Ross, A., Prabhakar, S., 2004. An Introduction to Biometric identification, IEEE Transaction on Circuits and Systems for Video Technology, vol.14, no.1, pp.4-20.
  • [7]. Şamlı, R., Yüksel, M. E., 2009. Biyometrik Güvenlik Sistemleri, Akademik Bilişim, Şanlıurfa-Türkiye.
  • [8]. Liu, S., Silverman, M., 2001. A Practical Guide to Biometric Security Technology, IT Professional, vol. 3, no. 1, pp. 27-32.
  • [9]. Unar, J., Senga, W., Abbasia, A., 2014. A Review of Biometric Technology Along with Trends and Prospects, Pattern identification, vol. 47, pp.2673-2688.
  • [10]. Monrose, F., Rubin, A., 1997. Authentication via Keystroke Dynamics, 4th ACM Conference on Computer and Communications Security, Switzerland, pp. 48-56.
  • [11]. http://www.biyolojisitesi.net/tum%20uniteler/denetleme_ve_duzenleme/gorme_nasil_gerceklesir.html, access: 6.1.2016.
  • [12]. Yücel, E. Işık, Renk ve Elektromanyetk Spektrum,http://www.akat.org/sizin_icin/elektromagnetik_tayf.pdf, access: 6.1.2016.
  • [13]. Alkoot, Fuad M., 2012. A Review On Advances In Iris identification Methods, International Journal of Computer Engineering Research, vol. 3(1), pp. 1-9, Kuwait.
  • [14]. http://www.biltek.tubitak.gov.tr/haberler/tip/s528_5.pdf, access: 6.1.2016.
  • [15]. Tasyapi Celebi A., Güllü, Kemal M., Ertürk, S., 2009. Low-complexity Iris identification Using One-bit Transform and Angular Radial Partitioning, 2009 IEEE 17th Signal Processing and Communications Applications Conference.
  • [16]. http://www.ergosis.com.tr/iris-tanima-teknolojisi.html, access: 6.1.2016.
  • [17]. Daugman, J., 2003. Demodulation by Comlex-Valued Wavelets for Stochastic Pattern identification, Int. J. Wavelets, Multi-Res. and ınfo. Processing. 1(1): 1-17.
  • [18]. Daugman, J., Downing, C., 1995. Demodulation, Predictive Coding and Spatial Vision, J. Opt. Soc. Am. A 12: 641-660.
  • [19]. Sanchez-Avila, C., Sanchez-Reillo, R., 2002. Iris-Based Biometric identification Using Dyadic Wavelet Transform, IEEE Aerosp. Electron. Sys. Mag., 17:3-6.
  • [20]. Lim, S., Lee, K., Byeon, O., Kim, T., 2001.Efficient İris identification Through İmprovement of Feature Vector and Classifier, ETRI J. 23(2): 1-70
  • [21]. Wildes, R., Asmuth, J., Green, G., Hsu, S., Kolczynski, R., Matey, J., McBride, S., 1996. A Machine-Vision System for Irıs identification, Mach. Vis. Applic., 9: 1-8.
  • [22]. Zhu, Y., Tan, T., Wang, Y., 2000. Biometric Personal identification Based On Iris Patterns, Int. Conf. Pattern identification, II:805-808.
  • [23]. Ma, L., 2003. Personal identification Based On Iris identification, Ph.D dissertation, China.
  • [24]. Jain, A., Ross, A., Nandakumar, K., İntroduction to Biometrics, https://books.google.com.tr/, access: 6.1.2016.
  • [25]. Wildes, R., 1994. A System for Automated Iris identification, 2nd IEEE Workshop Applicat. Comput. Vision, pp.121-128.
  • [26]. Jones, M. J., Guo, G., 2008. Iris Extraction Based on Intensity Gradient and Texture Difference, IEEE Workshop on Applications of Computer Vision Conference.
  • [27]. Ziauddin, S., Dailey M., 2010. Robust Iris Verification for Key Management, Pattern identification Letters, 31(9).
  • [28]. Perez, C. A., Aravena, C. M., Vallejos, J. I., Estevez, P. A., Held, C. M. 2010.Face and Iris Localization Using Templates Designed by Particle Swarm Optimization, Pattern identification Letters, 31(9): 857-868.
  • [29]. Lim, S., Lee, K., Byeon, O., Kim, T., 2001. Efficient Iris identification Through Improvement of Feature Vector and Classifier. ETRI J. 23(2): 1-70.
  • [30]. Boles, W., Boashash, B., 1998. A Human identification Technique Using Images of Iris and Wavelet Transform, IEEE Transaction on Signal Processing, 46(4).
Yıl 2017, Cilt: 2 Sayı: 1, 167 - 180, 25.02.2017

Öz

Kaynakça

  • [1]. Turhan C., Ceyhan, E., Sağıroğlu Ş., Biyometrik Sistemlerde Güvenlik Üzerine Bir İnceleme, www.iscturkey.org, access: 03.03.2016.
  • [2]. Yalçın, N., Gürbüz, F., 2015. Biyometrik Güvenlik Sistemlerinin İncelenmesi, Düzce Üniversitesi Bilim ve Teknoloji Dergisi, cilt 3, no. 2, pp.
  • [3]. Elumalai, K., Kannan, M., 2011. Multimodal Authentication For High End Security, International Journal on Computer Science and Engineering (IJCSE), 3(2), 687-692.
  • [4]. Jain, K., Bolle, R., Pankanti, S., 1999. Biometrics: Personal identification in Networked Society, Springer Science and Business Media.
  • [5]. Ergen, B., Çalışkan, A., 2011. Biyometrik Sistemler ve El Tabanlı Biyometrik Tanıma Karakteristikleri, 6th International Advanced Technologies Symposium, Elazığ-Türkiye.
  • [6]. Jain, A.K., Ross, A., Prabhakar, S., 2004. An Introduction to Biometric identification, IEEE Transaction on Circuits and Systems for Video Technology, vol.14, no.1, pp.4-20.
  • [7]. Şamlı, R., Yüksel, M. E., 2009. Biyometrik Güvenlik Sistemleri, Akademik Bilişim, Şanlıurfa-Türkiye.
  • [8]. Liu, S., Silverman, M., 2001. A Practical Guide to Biometric Security Technology, IT Professional, vol. 3, no. 1, pp. 27-32.
  • [9]. Unar, J., Senga, W., Abbasia, A., 2014. A Review of Biometric Technology Along with Trends and Prospects, Pattern identification, vol. 47, pp.2673-2688.
  • [10]. Monrose, F., Rubin, A., 1997. Authentication via Keystroke Dynamics, 4th ACM Conference on Computer and Communications Security, Switzerland, pp. 48-56.
  • [11]. http://www.biyolojisitesi.net/tum%20uniteler/denetleme_ve_duzenleme/gorme_nasil_gerceklesir.html, access: 6.1.2016.
  • [12]. Yücel, E. Işık, Renk ve Elektromanyetk Spektrum,http://www.akat.org/sizin_icin/elektromagnetik_tayf.pdf, access: 6.1.2016.
  • [13]. Alkoot, Fuad M., 2012. A Review On Advances In Iris identification Methods, International Journal of Computer Engineering Research, vol. 3(1), pp. 1-9, Kuwait.
  • [14]. http://www.biltek.tubitak.gov.tr/haberler/tip/s528_5.pdf, access: 6.1.2016.
  • [15]. Tasyapi Celebi A., Güllü, Kemal M., Ertürk, S., 2009. Low-complexity Iris identification Using One-bit Transform and Angular Radial Partitioning, 2009 IEEE 17th Signal Processing and Communications Applications Conference.
  • [16]. http://www.ergosis.com.tr/iris-tanima-teknolojisi.html, access: 6.1.2016.
  • [17]. Daugman, J., 2003. Demodulation by Comlex-Valued Wavelets for Stochastic Pattern identification, Int. J. Wavelets, Multi-Res. and ınfo. Processing. 1(1): 1-17.
  • [18]. Daugman, J., Downing, C., 1995. Demodulation, Predictive Coding and Spatial Vision, J. Opt. Soc. Am. A 12: 641-660.
  • [19]. Sanchez-Avila, C., Sanchez-Reillo, R., 2002. Iris-Based Biometric identification Using Dyadic Wavelet Transform, IEEE Aerosp. Electron. Sys. Mag., 17:3-6.
  • [20]. Lim, S., Lee, K., Byeon, O., Kim, T., 2001.Efficient İris identification Through İmprovement of Feature Vector and Classifier, ETRI J. 23(2): 1-70
  • [21]. Wildes, R., Asmuth, J., Green, G., Hsu, S., Kolczynski, R., Matey, J., McBride, S., 1996. A Machine-Vision System for Irıs identification, Mach. Vis. Applic., 9: 1-8.
  • [22]. Zhu, Y., Tan, T., Wang, Y., 2000. Biometric Personal identification Based On Iris Patterns, Int. Conf. Pattern identification, II:805-808.
  • [23]. Ma, L., 2003. Personal identification Based On Iris identification, Ph.D dissertation, China.
  • [24]. Jain, A., Ross, A., Nandakumar, K., İntroduction to Biometrics, https://books.google.com.tr/, access: 6.1.2016.
  • [25]. Wildes, R., 1994. A System for Automated Iris identification, 2nd IEEE Workshop Applicat. Comput. Vision, pp.121-128.
  • [26]. Jones, M. J., Guo, G., 2008. Iris Extraction Based on Intensity Gradient and Texture Difference, IEEE Workshop on Applications of Computer Vision Conference.
  • [27]. Ziauddin, S., Dailey M., 2010. Robust Iris Verification for Key Management, Pattern identification Letters, 31(9).
  • [28]. Perez, C. A., Aravena, C. M., Vallejos, J. I., Estevez, P. A., Held, C. M. 2010.Face and Iris Localization Using Templates Designed by Particle Swarm Optimization, Pattern identification Letters, 31(9): 857-868.
  • [29]. Lim, S., Lee, K., Byeon, O., Kim, T., 2001. Efficient Iris identification Through Improvement of Feature Vector and Classifier. ETRI J. 23(2): 1-70.
  • [30]. Boles, W., Boashash, B., 1998. A Human identification Technique Using Images of Iris and Wavelet Transform, IEEE Transaction on Signal Processing, 46(4).
Toplam 30 adet kaynakça vardır.

Ayrıntılar

Konular Mühendislik
Bölüm Makaleler
Yazarlar

Yesim Ulgen Sonmez

Yayımlanma Tarihi 25 Şubat 2017
Yayımlandığı Sayı Yıl 2017 Cilt: 2 Sayı: 1

Kaynak Göster

APA Ulgen Sonmez, Y. (2017). Research on Retinal and Iris Identification Systems. European Journal of Engineering and Natural Sciences, 2(1), 167-180.
AMA Ulgen Sonmez Y. Research on Retinal and Iris Identification Systems. European Journal of Engineering and Natural Sciences. Şubat 2017;2(1):167-180.
Chicago Ulgen Sonmez, Yesim. “Research on Retinal and Iris Identification Systems”. European Journal of Engineering and Natural Sciences 2, sy. 1 (Şubat 2017): 167-80.
EndNote Ulgen Sonmez Y (01 Şubat 2017) Research on Retinal and Iris Identification Systems. European Journal of Engineering and Natural Sciences 2 1 167–180.
IEEE Y. Ulgen Sonmez, “Research on Retinal and Iris Identification Systems”, European Journal of Engineering and Natural Sciences, c. 2, sy. 1, ss. 167–180, 2017.
ISNAD Ulgen Sonmez, Yesim. “Research on Retinal and Iris Identification Systems”. European Journal of Engineering and Natural Sciences 2/1 (Şubat 2017), 167-180.
JAMA Ulgen Sonmez Y. Research on Retinal and Iris Identification Systems. European Journal of Engineering and Natural Sciences. 2017;2:167–180.
MLA Ulgen Sonmez, Yesim. “Research on Retinal and Iris Identification Systems”. European Journal of Engineering and Natural Sciences, c. 2, sy. 1, 2017, ss. 167-80.
Vancouver Ulgen Sonmez Y. Research on Retinal and Iris Identification Systems. European Journal of Engineering and Natural Sciences. 2017;2(1):167-80.