Abstract
Near infrared (NIR) imaging is one of the promising methods for identification of superficial veins and widely researched and used in clinical medicine and biomedical studies. However, just like imaging in visible spectrum, NIR imaging is not adequate for exact recognition of the vein system as it is, therefore nearly every research starts with preprocessing to prepare the images for identification. Two major filtering methods are anisotropic diffusion and Gaussian high-pass filter which both consist of mandatory parametric adjustments for better visualization of the images and for revealing the vein system. Therefore in this paper we deal with parametric variations of these two methods on a NIR image to give ideas for choosing proper preprocessing techniques and parameters, excluding edge detection and vein detection methodologies.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Fredembach, C.: Near-infrared imaging. http://ivrl.epfl.ch/research/infrared/imaging. Accessed 14 Jan 2018
Cope, M., Delpy, D.T.: System for long-term measurement of cerebral blood and tissue oxygenation on newborn infants by near infra-red transillumination. Med. Biol. Eng. Comput. 26(3), 289–294 (1988)
Xueyan, L., Shuxu, G.: The fourth biometric - vein recognition. In: Yin, P.-Y. (ed.) Pattern Recognition Techniques, Technology and Applications (2008)
Bouzida, N., Bendada, A.H., Maldague, X.P.: Near-infrared image formation and processing for the extraction of hand veins. J. Mod. Opt. 57(18), 1731–1737 (2010)
Wang, L., Leedham, G., Cho, S.Y.: Infrared imaging of hand vein patterns for biometric purposes. IET Comput. Vis. 1(3), 113–122 (2007)
Van Tien, T., Mien, P.T.H., Dung, P.T., Linh, H.Q.: Using near-infrared technique for vein imaging. In: Toi, V.V., Lien Phuong, T.H. (eds.) 5th International Conference on Biomedical Engineering in Vietnam. IP, vol. 46, pp. 190–193. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-11776-8_46
Paquit, V., Price, J.R., Seulin, R., Mériaudeau, F., Farahi, R.H., Tobin, K.W., Ferrell, T.L.: Near-infrared imaging and structured light ranging for automatic catheter insertion. In: Medical Imaging 2006: Visualization, Image-Guided Procedures, and Display (2006)
Alpar, O., Krejcar, O.: Superficial dorsal hand vein estimation. In: Rojas, I., Ortuño, F. (eds.) IWBBIO 2017. LNCS, vol. 10208, pp. 408–418. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-56148-6_36
Alpar, O., Krejcar, O.: Quantization and equalization of pseudocolor images in hand thermography. In: Rojas, I., Ortuño, F. (eds.) IWBBIO 2017. LNCS, vol. 10208, pp. 397–407. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-56148-6_35
Acknowledgement
The work and the contribution were supported by the SPEV project “Smart Solutions in Ubiquitous Computing Environments”, University of Hradec Kralove, Faculty of Informatics and Management, Czech Republic (under ID: UHK-FIM-SPEV-2018).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Kirimtat, A., Krejcar, O. (2018). Parametric Variations of Anisotropic Diffusion and Gaussian High-Pass Filter for NIR Image Preprocessing in Vein Identification. In: Rojas, I., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2018. Lecture Notes in Computer Science(), vol 10814. Springer, Cham. https://doi.org/10.1007/978-3-319-78759-6_20
Download citation
DOI: https://doi.org/10.1007/978-3-319-78759-6_20
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-78758-9
Online ISBN: 978-3-319-78759-6
eBook Packages: Computer ScienceComputer Science (R0)