Abstract
Recently more interest in retina-based human recognition is observable. It is connected with the fact that this biometrics trait can guarantee absolute certainty in the case of human identity. In the literature, one can easily observe that most of the algorithms are based on veins system and its pattern. A method to extract recently mentioned structure is presented in this paper. The proposed approach consists of three main parts: preprocessing, segmentation and unnecessary artifacts removal. During the research, the authors used different image processing methods for veins system extraction, especially diversified binarization algorithms and edge detection approaches were tested. In the time of the experiments the authors took into consideration not only accuracy but also proposed solution efficiency. Performed tests have shown that it is clearly possible to extract veins system with satisfactory precision and efficiency.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Vacca, J.R.: Biometric Technologies and Verification Systems. Butterworth-Heineman, pp. 85–87 (2007). ISBN 978-0750679671
https://www.scmagazineuk.com/starbugs-eyes-german-hacker-spoofs-iris-recognition/article/1479198. Accessed 15 Feb 2019
Hao, H., Kumar, D.K., Aliahmad, B., Che Azemin, M.Z., Kawasaki, R.: Using color histogram as the trait of retina biometric. In: 2013 IEEE ISSNIP Biosignals and Biorobotics Conference: Biosignals and Robotics for Better and Safer Living (BRC), Rio de Janerio, Brazil, 18–20 February, Proceedings (2013)
Nguyen, U.T.V., et al.: Automated quantification of retinal arteriovenous nicking from colour fundus images. In: 2013 IEEE 35th Annual International Conference of the IEEE EMBS, Osaka, Japan, 3–7 July, Proceedings, pp. 5865–5868 (2013)
Wan Mustafa, W.A.B., Yazid, H., Bin Yaacob, S., Bin Basah, S.N.: Blood vessel extraction using morphological operation for diabetic retinopathy. In: 2014 IEEE Region 10 Symposium, Kuala Lumpur, Malaysia, 14–16 April, Proceedings (2014)
Kar, S.S., Maity, S.P.: Extraction of retinal blood vessel using curvelet transform and fuzzy C-Means. In: 2014 IEEE 22nd International Conference on Pattern Recognition, Stockholm, Sweden, 24–28 August, Proceedings, pp. 3392–3397 (2014)
Chlabra, S., Bhusan, B.: Supervised pixel classification into arteries and veins of retinal images. In: 2014 IEEE International Conference on Innovative Applications of Computational Intelligence on Power, Energy and Controls with their Impact on Humanity, CIPECH 2014, Ghaziabad, India, 28–29 November, Proceedings, pp. 59–62 (2014)
Minar, J., Pinkava, M., Riha, K., Dutta, M.K., Sengar, N.: Automatic extraction of blood vessels and veins using laplace operator in fundus image. In: 2015 IEEE International Conference on Green Computing and Internet of Things (ICGCIoT), Noida, India, 8–10 October, Proceedings (2015)
Frucci, M., Riccio, D., Sanniti di Baja, G., Serino, L.: Using direction and score information for retina based person verification. Expert Syst. Appl. 94, 1–10 (2018)
Choraś, R.: Retina recognition for Biometrics. In: 7th International Conference on Digital Information Management (ICDIM), Macau, China, 22–24 August, Proceedings (2012)
Dhghani, A., Ghassabi, Z.R., Abrishami Moghaddam, H., Moin, M.-S.: Human recognition based on retinal images and using new similarity function. EURASIP J. Image Video Process. 58(1) (2013). https://doi.org/10.1186/1687-5281-2013-58
Szymkowski, M., Saeed, E., Saeed, K.: Retina tomography and optical coherence tomography in eye diagnostic system. In: Chaki, R., Cortesi, A., Saeed, K., Chaki, N. (eds.) Advanced Computing and Systems for Security. AISC, vol. 666, pp. 31–42. Springer, Singapore (2018). https://doi.org/10.1007/978-981-10-8180-4_3
Saeed, E., Szymkowski, M., Saeed, K., Mariak, Z.: An approach to automatic hard exudate detection in retina color images by telemedicine system based on d-Eye sensor and image processing algorithms. MDPI Sens. 19(3) (2019). https://doi.org/10.3390/s19030695
http://cecas.clemson.edu/~ahoover/stare/. Accessed 30 Dec 2018
https://www.isi.uu.nl/Research/Databases/DRIVE/. Accessed 30 Dec 2018
Xu, L., Luo, S.: A novel method for blood vessels detection from retinal images. BioMed. Eng. Online 9, 14 (2010)
Raja Sundhara Siva, D., Vasuki, S.: Automatic detection of blood vessels in retinal images for diabetic retinopathy diagnosis. Comput. Math. Methods Med. 2015, 12 (2015)
Zhang, J., Cui, Y., Jiang, W., Wang, L.: Blood vessels segmentation of retinal images based on neural network. In: 8th International Conference on Image and Graphics, 2015 ICIG, Tianjin, China, Proceedings, pp. 11–17 (2015)
Otsu, N.: A threshold selection method from gray-level histograms. IEEE Trans. Syst. Man Cybern. 9(1), 62–66 (1979)
Tabędzki, M., Saeed, K., Szczepański, A.: A modified K3M thinning algorithm. Int. J. Appl. Math. Comput. Sci. 26(2), 439–450 (2016)
Saxena, L.P.: Niblack’s binarization method and its modifications to real-time applications: a review. Artif. Intell. Rev. 51(4), 673–705 (2019)
Eyupoglu, C.: Implementation of Bernsen’s locally adaptive binarization method for gray scale images. In: 2016, Proceedings of 7th International Science and Technology Conference (ISTEC), pp. 621–625 (2016)
Zhang, T.Y., Suen, C.Y.: A fast parallel algorithm for thinning digital patterns. Commun. ACM 27(3), 236–239 (1984)
Acknowledgment
The authors are thankful to Medical University of Białystok, Faculty of Medicine, Department of Ophthalmology, especially to Dr Emil Saeed, for their support and providing a sample database.
This work was supported partially by grant S/WI/3/2018 and by grant WI/WI/2/2019 from Białystok University of Technology and funded with resources for research by the Ministry of Science and Higher Education in Poland.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Szymkowski, M., Najda, D., Saeed, K. (2019). An Algorithm for Exact Retinal Vein Extraction. In: Saeed, K., Chaki, R., Janev, V. (eds) Computer Information Systems and Industrial Management. CISIM 2019. Lecture Notes in Computer Science(), vol 11703. Springer, Cham. https://doi.org/10.1007/978-3-030-28957-7_7
Download citation
DOI: https://doi.org/10.1007/978-3-030-28957-7_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-28956-0
Online ISBN: 978-3-030-28957-7
eBook Packages: Computer ScienceComputer Science (R0)