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KIZILÖTESİ DAMAR GÖRÜNTÜSÜ İŞLEME VE DAMAR TESPİTİ

Yıl 2021, Cilt: 3 Sayı: 2, 183 - 188, 28.02.2021

Öz

Yüksek güvenlikli kişisel tanımlama giderek daha da önemli hale gelmektedir. Kimlik doğrulama için biyometrik imzalar kullanılmaktadır. Damar desenli kişisel doğrulama insan biyometrik imzalarından biridir. Damar desenli kişisel doğrulama güvenlik uygulamalarının yanında sağlık alanında da çok kullanılmaktadır. Obez kişilerin, koyu tenli kişilerin veya yanık vakaları gibi damarın bulunmasını zorlaştıran durumlarda tedavide veya muayenede güçlükler yaşanmaktadır. Kimlik doğrulamanın güvenilirliğini arttırmak ve sağlık alanındaki dezavantajları gidermek için birçok damar görüntüleme tekniği geliştirilmiştir. Bu çalışmada bu teknikler test edilmektedir. Gelecek çalışmalarda görüntü işleme yapılan görüntülerin ham görüntünün alındığı bölgeye geri yansıtılması hedeflenmektedir.

Kaynakça

  • A. Jain, R. Bolle, and S. Pankanti. (1999) Biometrics: Personal Identification In Networked Society, Kluwer Academic Publishers, Dordrecht.
  • Doniger, S.J., Ishimine, P., Fox, J.C., Kanegaye, J.T. (2009) Randomized controlled trial of ultrasound-guided peripheral intravenous catheter placement versus traditional techniques in difficult-access pediatric patients. Pediatr Emerg Care.
  • R. de Luis-Garcia, C. Alberola-Lopez, O. Aghzout, and J. Ruiz-Alzola, (2009) Biometric identification systems, Pattern Recognition, vol. 33, no. 3, pp. 7–10,
  • Rajalakshmi, M., Rega, P., Student, P. G., Salai, R. G. (2011) Research article vascular pattern recognition using clahe and median filterıng methods address for correspondence. International Journal of Advanced Engineering Technology,2:4:263-266.
  • Y. Wang, Y. Fan, W. Liao, K. Li, L.-K. Shark, and M. R. Varley, (2012) Hand vein recognition based on multiple keypoints sets, 2012 5th IAPR International Conference on Biometrics (ICB), pp. 367–371, Mar. 2012.
  • M. H.-. M. Khan, N. Ali, and M. Khan, (2009) A New Method to Extract Dorsal Hand Vein Pattern using Quadratic Inference Function, vol. 6, no. 3, pp. 26–30.
  • Saravanan, C. D. (2010) Color image to grayscale image conversion, Second International Conference on Computer Engineering and Applications. 2:196–199.
  • B. Sravani and M. V. Nageswara Rao, (2014) Removing of high density salt and pepper noise using fuzzy median filter, 2014 International Conference on High Performance Computing and Applications (ICHPCA), Bhubaneswar
  • S. Patel and M. Goswami, (2014) Comparative analysis of Histogram Equalization techniques, 2014 International Conference on Contemporary Computing and Informatics (IC3I), Mysore, 2014, pp. 167-168, doi: 10.1109/IC3I.2014.7019808.
  • Cayiroglu, İ., Ders Notları [PDF Belgesi] www.ibrahimcayiroglu.com
  • RYeltsin (2019, December). Finger Vein from https://www.kaggle.com/ryeltsin/finger-vein.
  • Bill Otto (2017) How many wavelengths, intensities and combinations are there physically? From https://www.quora.com/Are-there-three-colors-of-light-RGB-or-is-it-infinite

INFRARED VEIN IMAGE PROCESSING AND VEIN DETECTION

Yıl 2021, Cilt: 3 Sayı: 2, 183 - 188, 28.02.2021

Öz

High-security personal identification is becoming increasingly important. Biometric signatures are used for authentication. Vein patterned personal verification is one of the human biometric signatures. Vein patterned personal verification is used a lot in healthcare as well as security applications. There are difficulties in treatment or examination in cases where obese people, dark skin people, or burns such as burns make the vein difficult to find. Many vein imaging techniques have been developed to increase the reliability of authentication or to eliminate disadvantages in the health field. In this study, these techniques are tested. With the outputs of this study, in future studies, it is aimed to reflect the image processed images to the region where the raw image is taken.

Kaynakça

  • A. Jain, R. Bolle, and S. Pankanti. (1999) Biometrics: Personal Identification In Networked Society, Kluwer Academic Publishers, Dordrecht.
  • Doniger, S.J., Ishimine, P., Fox, J.C., Kanegaye, J.T. (2009) Randomized controlled trial of ultrasound-guided peripheral intravenous catheter placement versus traditional techniques in difficult-access pediatric patients. Pediatr Emerg Care.
  • R. de Luis-Garcia, C. Alberola-Lopez, O. Aghzout, and J. Ruiz-Alzola, (2009) Biometric identification systems, Pattern Recognition, vol. 33, no. 3, pp. 7–10,
  • Rajalakshmi, M., Rega, P., Student, P. G., Salai, R. G. (2011) Research article vascular pattern recognition using clahe and median filterıng methods address for correspondence. International Journal of Advanced Engineering Technology,2:4:263-266.
  • Y. Wang, Y. Fan, W. Liao, K. Li, L.-K. Shark, and M. R. Varley, (2012) Hand vein recognition based on multiple keypoints sets, 2012 5th IAPR International Conference on Biometrics (ICB), pp. 367–371, Mar. 2012.
  • M. H.-. M. Khan, N. Ali, and M. Khan, (2009) A New Method to Extract Dorsal Hand Vein Pattern using Quadratic Inference Function, vol. 6, no. 3, pp. 26–30.
  • Saravanan, C. D. (2010) Color image to grayscale image conversion, Second International Conference on Computer Engineering and Applications. 2:196–199.
  • B. Sravani and M. V. Nageswara Rao, (2014) Removing of high density salt and pepper noise using fuzzy median filter, 2014 International Conference on High Performance Computing and Applications (ICHPCA), Bhubaneswar
  • S. Patel and M. Goswami, (2014) Comparative analysis of Histogram Equalization techniques, 2014 International Conference on Contemporary Computing and Informatics (IC3I), Mysore, 2014, pp. 167-168, doi: 10.1109/IC3I.2014.7019808.
  • Cayiroglu, İ., Ders Notları [PDF Belgesi] www.ibrahimcayiroglu.com
  • RYeltsin (2019, December). Finger Vein from https://www.kaggle.com/ryeltsin/finger-vein.
  • Bill Otto (2017) How many wavelengths, intensities and combinations are there physically? From https://www.quora.com/Are-there-three-colors-of-light-RGB-or-is-it-infinite
Toplam 12 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Bilgisayar Yazılımı
Bölüm Araştırma Makaleleri
Yazarlar

Göksel Çankaya Bu kişi benim 0000-0001-6139-6588

Ali Boyacı 0000-0002-2553-1911

Serhan Yarkan 0000-0001-6430-3009

Yayımlanma Tarihi 28 Şubat 2021
Gönderilme Tarihi 1 Temmuz 2020
Yayımlandığı Sayı Yıl 2021 Cilt: 3 Sayı: 2

Kaynak Göster

APA Çankaya, G., Boyacı, A., & Yarkan, S. (2021). KIZILÖTESİ DAMAR GÖRÜNTÜSÜ İŞLEME VE DAMAR TESPİTİ. İstanbul Ticaret Üniversitesi Teknoloji Ve Uygulamalı Bilimler Dergisi, 3(2), 183-188.