Alexander V. Orlov
Kostroma State University
Evgeny L. Pashin
Kostroma State Argicultural Academy
Orlov A. V., Pashin E. L. Measuring thickness of flax fibres in a cluster using computer vision. Technologies & Quality. 2024. No 1(63). P. 5–11. (In Russ.) https: doi10.34216/2587-6147-2024-1-63-5-11.
DOI: https://doi.org/10.34216/2587-6147-2024-1-63-5-11
УДК: 677.017.4:620.171.3
Publish date: 2024-03-06
Annotation: Authors analyse a method of indirect measurement of flax fibre linear density using its thickness, based on computer vision approach and “distance transform” algorithm in particular. A number of flaws of this method are identified. The main reason for the discrepancy is the effect of crossed fibres within the analysed sample. The secondary reason is the specific shape of fibre’s topological skeletonnear its tips. Based on these observations, a software model of the problem has been created. The software produces a simplified image of crossed fibres with specified properties, and measures this image using the above method. The effect of various factors on the discrepancy in the distribution of thickness values appears to match well with theoretical analysis. Additionally, a number of ways to improve the software model are outlined, related to how typicallyfibres are oriented within the analysed sample.
Keywords: computer vision, linear density, bast fibre, distance transform, topological skeleton, crossing, software model
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Author's info: Alexander V. Orlov, Kostroma State University, Kostroma, Russia, aorlov@list.ru, https://orcid.org/0000-0002-4995-3393
Co-author's info: Evgeny L. Pashin, Kostroma State Argicultural Academy, Kostroma, Russia, evgpashin@yandex.ru, https://orcid.org/0000-0002-5871-874Х