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Particle Morphology Analysis of Biomass Material Based on Improved Image Processing Method
Particle morphology, including size and shape, is an important factor that significantly influences the physical and chemical properties of biomass material. Based on image processing technology, a method was developed to process sample images, measure particle dimensions, and analyse the particle s...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5337379/ https://www.ncbi.nlm.nih.gov/pubmed/28298925 http://dx.doi.org/10.1155/2017/5840690 |
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author | Lu, Zhaolin Hu, Xiaojuan Lu, Yao |
author_facet | Lu, Zhaolin Hu, Xiaojuan Lu, Yao |
author_sort | Lu, Zhaolin |
collection | PubMed |
description | Particle morphology, including size and shape, is an important factor that significantly influences the physical and chemical properties of biomass material. Based on image processing technology, a method was developed to process sample images, measure particle dimensions, and analyse the particle size and shape distributions of knife-milled wheat straw, which had been preclassified into five nominal size groups using mechanical sieving approach. Considering the great variation of particle size from micrometer to millimeter, the powders greater than 250 μm were photographed by a flatbed scanner without zoom function, and the others were photographed using a scanning electron microscopy (SEM) with high-image resolution. Actual imaging tests confirmed the excellent effect of backscattered electron (BSE) imaging mode of SEM. Particle aggregation is an important factor that affects the recognition accuracy of the image processing method. In sample preparation, the singulated arrangement and ultrasonic dispersion methods were used to separate powders into particles that were larger and smaller than the nominal size of 250 μm. In addition, an image segmentation algorithm based on particle geometrical information was proposed to recognise the finer clustered powders. Experimental results demonstrated that the improved image processing method was suitable to analyse the particle size and shape distributions of ground biomass materials and solve the size inconsistencies in sieving analysis. |
format | Online Article Text |
id | pubmed-5337379 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-53373792017-03-15 Particle Morphology Analysis of Biomass Material Based on Improved Image Processing Method Lu, Zhaolin Hu, Xiaojuan Lu, Yao Int J Anal Chem Research Article Particle morphology, including size and shape, is an important factor that significantly influences the physical and chemical properties of biomass material. Based on image processing technology, a method was developed to process sample images, measure particle dimensions, and analyse the particle size and shape distributions of knife-milled wheat straw, which had been preclassified into five nominal size groups using mechanical sieving approach. Considering the great variation of particle size from micrometer to millimeter, the powders greater than 250 μm were photographed by a flatbed scanner without zoom function, and the others were photographed using a scanning electron microscopy (SEM) with high-image resolution. Actual imaging tests confirmed the excellent effect of backscattered electron (BSE) imaging mode of SEM. Particle aggregation is an important factor that affects the recognition accuracy of the image processing method. In sample preparation, the singulated arrangement and ultrasonic dispersion methods were used to separate powders into particles that were larger and smaller than the nominal size of 250 μm. In addition, an image segmentation algorithm based on particle geometrical information was proposed to recognise the finer clustered powders. Experimental results demonstrated that the improved image processing method was suitable to analyse the particle size and shape distributions of ground biomass materials and solve the size inconsistencies in sieving analysis. Hindawi Publishing Corporation 2017 2017-02-19 /pmc/articles/PMC5337379/ /pubmed/28298925 http://dx.doi.org/10.1155/2017/5840690 Text en Copyright © 2017 Zhaolin Lu et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Lu, Zhaolin Hu, Xiaojuan Lu, Yao Particle Morphology Analysis of Biomass Material Based on Improved Image Processing Method |
title | Particle Morphology Analysis of Biomass Material Based on Improved Image Processing Method |
title_full | Particle Morphology Analysis of Biomass Material Based on Improved Image Processing Method |
title_fullStr | Particle Morphology Analysis of Biomass Material Based on Improved Image Processing Method |
title_full_unstemmed | Particle Morphology Analysis of Biomass Material Based on Improved Image Processing Method |
title_short | Particle Morphology Analysis of Biomass Material Based on Improved Image Processing Method |
title_sort | particle morphology analysis of biomass material based on improved image processing method |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5337379/ https://www.ncbi.nlm.nih.gov/pubmed/28298925 http://dx.doi.org/10.1155/2017/5840690 |
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