Parametric Variations of Anisotropic Diffusion and Gaussian High-Pass Filter for NIR Image Preprocessing in Vein Identification
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F18%3A50014708" target="_blank" >RIV/62690094:18450/18:50014708 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-319-78759-6_20" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-319-78759-6_20</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-78759-6_20" target="_blank" >10.1007/978-3-319-78759-6_20</a>
Alternative languages
Result language
angličtina
Original language name
Parametric Variations of Anisotropic Diffusion and Gaussian High-Pass Filter for NIR Image Preprocessing in Vein Identification
Original language description
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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture notes in computer science
ISBN
978-3-319-78758-9
ISSN
0302-9743
e-ISSN
neuvedeno
Number of pages
9
Pages from-to
212-220
Publisher name
Springer
Place of publication
Cham
Event location
Granada
Event date
Apr 25, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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