Hardwood Species Classification with Hyperspectral Microscopic Images

Joint Authors

Peng, Zhao
Wang, Cheng-Kun

Source

Journal of Spectroscopy

Issue

Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-14, 14 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2019-06-27

Country of Publication

Egypt

No. of Pages

14

Main Subjects

Physics

Abstract EN

We propose a hardwood species identification method based on wood hyperspectral microscopic images.

A SOC710VP hyperspectral stereomicroscope was used to acquire microscopic images of a hardwood cross section.

In these microscopic images, each part’s spectral features are discussed.

We found that the spectral divisibility of wood vessels’ peripheral and central regions in the hyperspectral microscopic images can be used for hardwood species recognition.

Mathematical morphological operation and K-L divergence were used to extract spectral features at the wood vessels’ peripheral regions and central regions, respectively.

By comparing wood vessels’ spectral similarity across wood species samples, we found that wood vessels’ peripheral spectral divisibility is larger than its central.

Finally, the spectral information from randomly selected regions of interest (i.e., ROI) and that of wood vessels’ peripheral and central regions have value as a classification basis.

In our hardwood species classification experiments, three dimensionality reduction algorithms, principal component analysis (PCA), kernel principal component analysis (KPCA), and multidimensional scaling (MDS), and the three classifiers, BP neural network, support vector machine (SVM), and Mahalanobis distance (MD), are combined to perform hardwood species classification work.

Experimental results indicate that the best recognition effect can be achieved at the peripheral region of wood vessels using PCA or MDS with the MD algorithm.

American Psychological Association (APA)

Peng, Zhao& Wang, Cheng-Kun. 2019. Hardwood Species Classification with Hyperspectral Microscopic Images. Journal of Spectroscopy،Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1191997

Modern Language Association (MLA)

Peng, Zhao& Wang, Cheng-Kun. Hardwood Species Classification with Hyperspectral Microscopic Images. Journal of Spectroscopy No. 2019 (2019), pp.1-14.
https://search.emarefa.net/detail/BIM-1191997

American Medical Association (AMA)

Peng, Zhao& Wang, Cheng-Kun. Hardwood Species Classification with Hyperspectral Microscopic Images. Journal of Spectroscopy. 2019. Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1191997

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1191997