Visual Abnormalities Detecting based on Similarity Matching
- https://doi.org/10.2991/tlicsc-18.2018.4How to use a DOI?
- Digital Image Processing, Pattern Recognition, Computer Vision, Abnormalities Detecting, Template matching.
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.
- © 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 - 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 - https://doi.org/10.2991/tlicsc-18.2018.4 ID - Yu2018/12 ER -