Identifying Wood Based on Near-Infrared Spectra and Four Gray-Level Co-Occurrence Matrix Texture Features

Pan, Xi; Li, Kang; Chen, Zhangjing; Yang, Zhong

doi:10.3390/f12111527

Cited by 14 publications

(2 citation statements)

References 23 publications

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“…The comparison of the results is also done via a database. The creation of the database is complicated by the lack of standards of the equipment, the software, the settings and the nature of the samples in the procedure [49,53]. The method is particularly suitable for determining the moisture content of wood in the mill [54].…”

Section: Passive Samplingmentioning

confidence: 99%

Systematics of Forestry Technology for Tracing the Timber Supply Chain

Kaulen,

Stopfer,

Lippert

et al. 2023

Forests

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Traceability is the ability to follow the processes that a raw material or product goes through. For forestry, this means identifying the wood from the standing tree to the mill entrance and recording all information about the technical (production) and spatial (transportation) manipulation of the timber by linking it to the ID. We reviewed the literature for developments in timber flow traceability. Findings range from disillusionment with the non-application of available forestry technology to enthusiasm for the advancement of technology that—given appropriate incentives of an economic, environmental, consumer-oriented and legislative nature—can rapidly lead to widespread end-to-end media-interruption-free implementation. Based on our research, the solution lies in optical biometric systems that identify the individual piece of wood—without attaching anything—at three crucial points: during assortment at the skid road, at the forest road and at the mill entrance. At all of these points, the data accruing during the timber supply process must be linked to the ID of the piece of wood via data management.

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Section: Passive Samplingmentioning

confidence: 99%

Systematics of Forestry Technology for Tracing the Timber Supply Chain

Kaulen,

Stopfer,

Lippert

et al. 2023

Forests

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show abstract

“…Figure 4 shows that the classification accuracy of transverse sections was higher than that of radial and tangential sections by using the above 6 feature classification methods. Pan et al (2021) concluded that GLCM incorporated with near-infrared (NIR) spectral features can rapidly identify wood, and that transverse sections contain more distinguishable wood features than the tangential and radial sections.…”

mentioning

confidence: 99%

Micro image classification of 19 high-value hardwood species based on texture feature fusion

Yang¹,

Jiang²,

Ma³

et al. 2023

BioRes

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For classification of wood species with similar microstructure, 19 high-value hardwood species of Papilionaceae, Ebenaceae, and Caesalpiniaceae were used as experimental objects. Images of transverse sections, radial sections, and tangential sections were collected by Micro CT. Local binary patterns (LBP) are often used for feature extraction. LBP deformed forms such as uniform LBP, rotation-invariant LBP, and rotation-invariant uniform LBP were fused with Gray-Level Co-Occurrence Matrix (GLCM) to form three fusion features. The fusion features were combined with support vector machine (SVM) or BP neural network to realize wood classification. The texture feature fusion method was found to be better than the single feature classification. Among them, the effect of uniform LBP and GLCM fusion was the best, and the classification accuracy combined with SVM was the highest. The evaluation of the classification of 19 kinds of hardwood mainly depended on transverse sections, and its accuracy was higher than that of the radial and tangential sections. Therefore, the classification results of transverse sections should be taken as the main evaluation basis for the classification of the 19 high-value hardwood species.

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A Review of the Applicability of Non-destructive Testing for the Determination of the Fire Performance of Reused Structural Timber

Uldry,

Husted,

Pope

et al. 2024

J Nondestruct Eval

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This paper presents a review of the possible methods for testing the fire performance properties of reused timber through non-destructive techniques, focusing on structural elements. Evaluating the fire performance of old wooden specimen is necessary to facilitate reuse, in the support of the transition to a circular economy. The use of non-destructive methods minimizes damages to the pieces during the evaluation process. Three angles are reviewed: (1) The properties of wood influencing fire performance, (2) the change of wood properties over time, and (3) the known non-destructive tests. Some properties of wood are known to influence the fire performance, e.g., the density. Of these, there is no evidence of irreversible changes due to the passage of time only. The many different non- and semi- destructive techniques that can be applied to wood seldom relate to these properties, but rather to mechanical properties or geometry. Additionally, accurate measurements are often difficult, while some are only done in laboratories. This review concludes that currently there is no known non-destructive method that permits to estimate the fire performance of a reused timber element compared to a new one. There is a gap of knowledge on the evolution of the fire properties of timber during the use phase of the building, and there are no established methods to test for these properties without destroying a significant portion of the element. Development of non-destructive test methodologies to assess fire properties of timber will expand the market for reused timber to include load carrying timber.

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Identifying Wood Based on Near-Infrared Spectra and Four Gray-Level Co-Occurrence Matrix Texture Features

Cited by 14 publications

References 23 publications

Systematics of Forestry Technology for Tracing the Timber Supply Chain

Systematics of Forestry Technology for Tracing the Timber Supply Chain

Micro image classification of 19 high-value hardwood species based on texture feature fusion

A Review of the Applicability of Non-destructive Testing for the Determination of the Fire Performance of Reused Structural Timber

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