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Paper Abstract and Keywords
Presentation 2024-02-20 13:15
DoG-PaDiM:Anomaly Detection with Defect Size Selectivity based on Bandpass Filtering
Naoto Hiramatsu, Naoki Murakami, Hiroki Kobayashi, Shuichi Akizuki, Manabu Hashimoto (Chukyo Univ.) ITS2023-69 IE2023-58
Abstract (in Japanese) (See Japanese page) 
(in English) In the background of the increasing precision of visual inspections, recently, anomaly detection methods using machine learning have been attracting attention. In particular, the PaDiM algorithm is simple and has been reported to be highly accurate in experiments using MVTecAD. However, this algorithm cannot specify arbitrarily the size of the defect area to be detected. Therefore, it is difficult to apply this algorithm to sites where anomalies of a specific size need to be detected. Therefore, this paper proposes a DoG-PaDiM that incorporates a DoG (Difference of Gaussian) filter with bandpass characteristics into the feature extraction part of PaDiM. Highly sensitive anomaly detection at specific spatial frequencies is realized by the effect of multi-stage DoG. Quantitative evaluation of the five texture datasets included in MVTecAD confirmed an average pixel ROC-AUC of 97.3, a 0.7 improvement over the original PaDiM results (96.6).
Keyword (in Japanese) (See Japanese page) 
(in English) Visual inspection / Anomaly detection / PaDiM / DoG filter / Bandpass / Difference of Gaussian / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 381, IE2023-58, pp. 124-129, Feb. 2024.
Paper # IE2023-58 
Date of Issue 2024-02-12 (ITS, IE) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF ITS2023-69 IE2023-58

Conference Information
Committee ITS IE ITE-MMS ITE-ME ITE-AIT  
Conference Date 2024-02-19 - 2024-02-20 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Image Processing, etc. 
Paper Information
Registration To IE 
Conference Code 2024-02-ITS-IE-MMS-ME-AIT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) DoG-PaDiM:Anomaly Detection with Defect Size Selectivity based on Bandpass Filtering 
Sub Title (in English)  
Keyword(1) Visual inspection  
Keyword(2) Anomaly detection  
Keyword(3) PaDiM  
Keyword(4) DoG filter  
Keyword(5) Bandpass  
Keyword(6) Difference of Gaussian  
Keyword(7)  
Keyword(8)  
1st Author's Name Naoto Hiramatsu  
1st Author's Affiliation Chukyo University (Chukyo Univ.)
2nd Author's Name Naoki Murakami  
2nd Author's Affiliation Chukyo University (Chukyo Univ.)
3rd Author's Name Hiroki Kobayashi  
3rd Author's Affiliation Chukyo University (Chukyo Univ.)
4th Author's Name Shuichi Akizuki  
4th Author's Affiliation Chukyo University (Chukyo Univ.)
5th Author's Name Manabu Hashimoto  
5th Author's Affiliation Chukyo University (Chukyo Univ.)
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Speaker Author-1 
Date Time 2024-02-20 13:15:00 
Presentation Time 15 minutes 
Registration for IE 
Paper # ITS2023-69, IE2023-58 
Volume (vol) vol.123 
Number (no) no.380(ITS), no.381(IE) 
Page pp.124-129 
#Pages 6 
Date of Issue 2024-02-12 (ITS, IE) 

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