Paper Abstract and Keywords |
Presentation |
2023-03-02 10:35
Investigation of Appearance Inspection Method Considering the Number of Corresponding Local Patches Katsuhisa Kitaguchi, Yohei Nishizaki, Mamoru Saito (ORIST) PRMU2022-74 IBISML2022-81 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
There has been a great deal of research on appearance inspection using deep learning, which learns only from normal images. Recently, datasets incorporating not only structural anomalies such as scratches and stains, but also logical anomalies such as wrong number of parts and wrong combination of parts have been released, and there is a need to deal with such anomalies. In this study, we propose that PatchCore, a SOTA method for structural anomalies, can deal with logical anomalies by adding the consideration of consistency in the number of patches. Specifically, the histograms of the features of the test image and the good image are compared, and if there is a difference, it is considered as an anomaly. Experiments are conducted on a set of images with logical anomalies added to MVTec AD to verify the effectiveness of the proposed method. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Visual inspection / Anomaly Detection / Deep Learning / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 122, no. 404, PRMU2022-74, pp. 88-92, March 2023. |
Paper # |
PRMU2022-74 |
Date of Issue |
2023-02-23 (PRMU, IBISML) |
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) |
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PRMU2022-74 IBISML2022-81 |
Conference Information |
Committee |
PRMU IBISML IPSJ-CVIM |
Conference Date |
2023-03-02 - 2023-03-03 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Future University Hakodate |
Topics (in Japanese) |
(See Japanese page) |
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Paper Information |
Registration To |
PRMU |
Conference Code |
2023-03-PRMU-IBISML-CVIM |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Investigation of Appearance Inspection Method Considering the Number of Corresponding Local Patches |
Sub Title (in English) |
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Keyword(1) |
Visual inspection |
Keyword(2) |
Anomaly Detection |
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Deep Learning |
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1st Author's Name |
Katsuhisa Kitaguchi |
1st Author's Affiliation |
Osaka Research Institure of Industrial Science and Technology (ORIST) |
2nd Author's Name |
Yohei Nishizaki |
2nd Author's Affiliation |
Osaka Research Institure of Industrial Science and Technology (ORIST) |
3rd Author's Name |
Mamoru Saito |
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Osaka Research Institure of Industrial Science and Technology (ORIST) |
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Speaker |
Author-1 |
Date Time |
2023-03-02 10:35:00 |
Presentation Time |
10 minutes |
Registration for |
PRMU |
Paper # |
PRMU2022-74, IBISML2022-81 |
Volume (vol) |
vol.122 |
Number (no) |
no.404(PRMU), no.405(IBISML) |
Page |
pp.88-92 |
#Pages |
5 |
Date of Issue |
2023-02-23 (PRMU, IBISML) |
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