Microwave tomography sensing for potential agarwood trees imaging
Agarwood or its scientific name, Aquilaria is an expensive and precious non-timber forest product. The problems faced by the agarwood industry are the indiscriminate harvesting of agarwood and ineffective identification and inspection process of Aquilaria tree by agarwood prospectors and researchers...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Published: |
Elsevier B.V.
2019
|
| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/89459/ http://dx.doi.org/10.1016/j.compag.2019.104901 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Agarwood or its scientific name, Aquilaria is an expensive and precious non-timber forest product. The problems faced by the agarwood industry are the indiscriminate harvesting of agarwood and ineffective identification and inspection process of Aquilaria tree by agarwood prospectors and researchers. Hence, microwave tomography (MWT) is proposed to evaluate agarwood in order to encounter these problems. This technique operates in a safe, non-invasive and insensitive to environmental impacts. A simulation-based study had been performed in which 16 antennas microwave tomography system was modelled using the finite element analysis. In this study, six profiles were being tested and simulated at 1 GHz. An electric field was simulated based on transverse electric mode to be emitted into the modelled wood with agarwood. Besides, electric field at the receiving antennas was also simulated when the simulated incident field was emitted into the modelled wood. The readings of the electric field for both incidents and receiving antennas were recorded to find the difference of electric field which will be used for image reconstruction. The images for the six profiles were reconstructed using Linear Back Projection (LBP), Filtered Back Projection (FBP), Newton's One-Step Error Reconstruction (NOSER) and Tikhonov Regularization (TR) image reconstruction algorithms. The reconstructed images were then analysed using the Mean Structural Similarity (MSSIM) index. The phantom and reconstructed images were analysed qualitatively and quantitatively. The findings showed promising results as the proposed MWT was able to distinguish and identify agarwood in Aquilaria tree. |
|---|