Proceedings of the 2018 International Conference on Mechanical, Electrical, Electronic Engineering & Science (MEEES 2018)

Study on Image Recognition and Classification of Wood Skin Defects Based on BOW Model

Authors
Fan Yang, Yuzeng Wang
Corresponding Author
Fan Yang
Available Online May 2018.
DOI
10.2991/meees-18.2018.16How to use a DOI?
Keywords
wood skin defect, image recognition, feature extraction, BOW model, support vector machine.
Abstract

To solve the problem of wood skin recognition and classification in wood processing industry, a method based on BOW model for image recognition of wood skin defects is proposed. First, we extract the HOG feature of wood skin defect image, and then build the BOW model to describe the wood skin defect image. Finally, we use different kernel functions combined with support vector machine (SVM) to identify the types of wood skin defects. The experimental results show that the average recognition rate of the proposed method is 85.4% for wood skin defect image recognition and classification, indicating that the BOW model is effective and feasible for wood skin defect image recognition and classification.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 International Conference on Mechanical, Electrical, Electronic Engineering & Science (MEEES 2018)
Series
Advances in Engineering Research
Publication Date
May 2018
ISBN
10.2991/meees-18.2018.16
ISSN
2352-5401
DOI
10.2991/meees-18.2018.16How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Fan Yang
AU  - Yuzeng Wang
PY  - 2018/05
DA  - 2018/05
TI  - Study on Image Recognition and Classification of Wood Skin Defects Based on BOW Model
BT  - Proceedings of the 2018 International Conference on Mechanical, Electrical, Electronic Engineering & Science (MEEES 2018)
PB  - Atlantis Press
SP  - 80
EP  - 84
SN  - 2352-5401
UR  - https://doi.org/10.2991/meees-18.2018.16
DO  - 10.2991/meees-18.2018.16
ID  - Yang2018/05
ER  -