Journal of Robotics, Networking and Artificial Life

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Volume 8, Issue 2, September 2021, Pages 127 - 133

A No-Reference Image Quality Assessment Metric for Wood Images

Authors
Heshalini Rajagopal1, *, Norrima Mokhtar1, Anis Salwa Mohd Khairuddin1, Wan Khairunizam2, Zuwairie Ibrahim3, Asrul Bin Adam3, Wan Amirul Bin Wan Mohd Mahiyidin1
1Department of Electrical Engineering, Faculty of Engineering, University of Malaya, Malaysia
2School of Mechatronic Engineering, University of Malaysia Perlis, Malaysia
3College of Engineering, University of Malaysia Pahang, Malaysia
*Corresponding author. Email: heshalini@gmail.com
Corresponding Author
Heshalini Rajagopal
Received 19 October 2020, Accepted 1 June 2021, Available Online 26 July 2021.
DOI
10.2991/jrnal.k.210713.012How to use a DOI?
Keywords
Wood images; GLCM; Gabor; GGNR-IQA; NR-IQA
Abstract

Image Quality Assessment (IQA) is a vital element in improving the efficiency of an automatic recognition system of various wood species. There is a need to develop a No-Reference IQA (NR-IQA) system as a perfect and distortion free wood images may be impossible to be acquired in the dusty environment in timber factories. To the best of our knowledge, there is no NR-IQA developed for wood images specifically. Therefore, a Gray Level Co-Occurrence Matrix (GLCM) and Gabor features-based NR-IQA (GGNR-IQA) metric is proposed to assess the quality of wood images. The proposed metric is developed by training the support vector machine regression with GLCM and Gabor features calculated for wood images together with scores obtained from subjective evaluation. The proposed IQA metric is compared with a widely used NR-IQA metric, Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE) and Full Reference-IQA (FR-IQA) metrics. Results shows that the proposed NR-IQA metric outperforms the BRISQUE and the FR-IQA metrics. Moreover, the proposed NR-IQA metric is beneficial in wood industry as a distortion free reference image is not needed to evaluate the wood images.

Copyright
© 2021 The Authors. Published by Atlantis Press International B.V.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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<Previous Article In Issue
Next Article In Issue>
Journal
Journal of Robotics, Networking and Artificial Life
Volume-Issue
8 - 2
Pages
127 - 133
Publication Date
2021/07/26
ISSN (Online)
2352-6386
ISSN (Print)
2405-9021
DOI
10.2991/jrnal.k.210713.012How to use a DOI?
Copyright
© 2021 The Authors. Published by Atlantis Press International B.V.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - JOUR
AU  - Heshalini Rajagopal
AU  - Norrima Mokhtar
AU  - Anis Salwa Mohd Khairuddin
AU  - Wan Khairunizam
AU  - Zuwairie Ibrahim
AU  - Asrul Bin Adam
AU  - Wan Amirul Bin Wan Mohd Mahiyidin
PY  - 2021
DA  - 2021/07/26
TI  - A No-Reference Image Quality Assessment Metric for Wood Images
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 127
EP  - 133
VL  - 8
IS  - 2
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.k.210713.012
DO  - 10.2991/jrnal.k.210713.012
ID  - Rajagopal2021
ER  -