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Effect of paper porosity on OCT images: Monte Carlo studyстатья
Информация о цитировании статьи получена из
Web of Science,
Scopus
Дата последнего поиска статьи во внешних источниках: 19 июля 2013 г.
- Авторы: Kirillin Mikhail Yu, Priezzhev Alexander V., Risto Myllylä
- Сборник: Advanced Laser Technologies 2007
- Серия: Proc. SPIE
- Том: 7022
- Год издания: 2007
- Издательство: SPIE
- Местоположение издательства: Bellingham, WA, United States
- Первая страница: 702214
- DOI: 10.1117/12.804102
- Аннотация: Non-invasive measurement of paper porosity is an important problem for papermaking industry. Presently used techniques are invasive and require long time for processing the sample. In recent years optical coherence tomography (OCT) has been proved to be an effective tool for non-invasive study of optically non-uniform scattering media including paper. The aim of present work is to study the potential ability of OCT for sensing the porosity of a paper sample by means of numerical simulations. The paper sample is characterized by variation of porosity along the sample while numerical simulations allow one to consider the samples with constant porosity which is useful for evaluation of the technique abilities. The calculations were performed implementing Monte Carlo-based technique developed earlier for simulation of OCT signals from multilayer paper models. A 9-layer model of paper consisting of five fiber layers and four air layers with non-planar boundaries was considered. The porosity of the samples was varied from 30 to 80% by varying the thicknesses of the layers. The simulations were performed for model paper samples without and with optical clearing agents (benzyl alcohol, 1-pentanol, isopropanol) applied. It was shown that the simulated OCT images of model paper with various porosities significantly differ revealing the potentiality of the OCT technique for sensing the porosity. When obtaining the images of paper samples with optical clearing agents applied, the inner structure of the samples is also revealed providing additional information about the samples under study.
- Добавил в систему: Приезжев Александр Васильевич