No-reference quality assessment for image-based assessment of economically important tropical woods
Image Quality Assessment (IQA) is essential for the accuracy of systems for automatic recognition of tree species for wood samples. In this study, a No-Reference IQA (NR-IQA), wood NR-IQA (WNR-IQA) metric was proposed to assess the quality of wood images. Support Vector Regression (SVR) was trained...
Saved in:
Main Authors: | Rajagopal, Heshalini, Mokhtar, Norrima, Tengku Mohmed Noor Izam, Tengku Faiz, Wan Ahmad, Wan Khairunizam |
---|---|
Format: | Article |
Published: |
Public Library of Science
2020
|
Subjects: | |
Online Access: | http://eprints.um.edu.my/25348/ https://doi.org/10.1371/journal.pone.0233320 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A no-reference image quality assessment metric for wood images
by: Rajagopal, Heshalini, et al.
Published: (2021) -
A no-reference image quality assessment metric for wood images
by: Heshalini, Rajagopal, et al.
Published: (2021) -
Gray Level Co-Occurrence Matrix (GLCM) and Gabor Features Based No-Reference Image Quality Assessment for Wood Images
by: Heshalini, Rajagopal, et al.
Published: (2021) -
Gray Level Co-Occurrence Matrix (GLCM) and Gabor features based No-Reference Image Quality Assessment for wood images
by: Rajagopal, Heshalini, et al.
Published: (2021) -
Development of quality assessment methods for wood images / Heshalini Rajagopal @ Ramasamy
by: Heshalini , Rajagopal @ Ramasamy
Published: (2021)