Proceedings of the 2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018)

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Visual Abnormalities Detecting based on Similarity Matching

Authors
Liuchuan Yu, Erjing Zhou, Baomin Xu, Shuangyuan Yu
Corresponding Author
Liuchuan Yu
Available Online December 2018.
DOI
10.2991/tlicsc-18.2018.4How to use a DOI?
Keywords
Digital Image Processing, Pattern Recognition, Computer Vision, Abnormalities Detecting, Template matching.
Abstract

Abnormalities detecting is one important application in the field of image processing and pattern recognition. It can alleviate human workload and improve productivity that employing computer graphic image theory and image processing technology analyzes and matches images in order to detect the abnormal region in image which has broad application prospects. In this paper, we propose a new abnormality detecting method based on similarity matching to address whether either missing or error abnormalities existing in bound books in industrial situation. First of all, we denoise the image by means of digital image processing and transformation, extract the sub rectangular region containing bound books using contour matching and locate the area exactly matching the template image using template matching. After that, we get a binary denoised image to detect the missing abnormality and the error abnormality using shape matching. In addition, we introduce some thresholds to improve the performance. The experiments show that the method we proposed achieve a better or the same performance comparing with the state-of-the-art methods.

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 Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018)
Series
Advances in Intelligent Systems Research
Publication Date
December 2018
ISBN
10.2991/tlicsc-18.2018.4
ISSN
1951-6851
DOI
10.2991/tlicsc-18.2018.4How 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

risenwbib
TY  - CONF
AU  - Liuchuan Yu
AU  - Erjing Zhou
AU  - Baomin Xu
AU  - Shuangyuan Yu
PY  - 2018/12
DA  - 2018/12
TI  - Visual Abnormalities Detecting based on Similarity Matching
BT  - Proceedings of the 2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018)
PB  - Atlantis Press
SP  - 17
EP  - 21
SN  - 1951-6851
UR  - https://doi.org/10.2991/tlicsc-18.2018.4
DO  - 10.2991/tlicsc-18.2018.4
ID  - Yu2018/12
ER  -