Paper Abstract and Keywords |
Presentation |
2021-03-04 13:50
Study of automatic masking method of locality on the plant specimen image based on the arrangement pattern of the text detection result Depeng Zhang, Yasuhiko Higaki, Yasuo Sugai (Chiba Univ.) LOIS2020-49 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
When plant specimens are published, the locality of endangered species cannot be disclosed. Images with specimen labels describing the collection points must be covered. So far, the text detection network CTPN has been used to detect the text on the sample and try to identify the location of the label, but due to false detection and the influence of characters other than the label, sufficient results have not been obtained. In low-resolution sample photos, it is difficult to directly detect the target to be masked using text recognition after text detection. Therefore, in this study, after performing text detection processing on the sample image, deleting the error detection and arranging the text box according to the characteristics of the plant specimen image, the method of identifying the target to be covered from the arrangement pattern was discussed. The results show that the method is effective. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Plant specimen image / Deep learning / Automatic masking / Text detection / CTPN / / / |
Reference Info. |
IEICE Tech. Rep., vol. 120, no. 417, LOIS2020-49, pp. 12-17, March 2021. |
Paper # |
LOIS2020-49 |
Date of Issue |
2021-02-25 (LOIS) |
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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LOIS2020-49 |
Conference Information |
Committee |
LOIS |
Conference Date |
2021-03-04 - 2021-03-04 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online |
Topics (in Japanese) |
(See Japanese page) |
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Paper Information |
Registration To |
LOIS |
Conference Code |
2021-03-LOIS |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Study of automatic masking method of locality on the plant specimen image based on the arrangement pattern of the text detection result |
Sub Title (in English) |
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Plant specimen image |
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Deep learning |
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Automatic masking |
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Text detection |
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CTPN |
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1st Author's Name |
Depeng Zhang |
1st Author's Affiliation |
Chiba University (Chiba Univ.) |
2nd Author's Name |
Yasuhiko Higaki |
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Chiba University (Chiba Univ.) |
3rd Author's Name |
Yasuo Sugai |
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Chiba University (Chiba Univ.) |
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Speaker |
Author-1 |
Date Time |
2021-03-04 13:50:00 |
Presentation Time |
25 minutes |
Registration for |
LOIS |
Paper # |
LOIS2020-49 |
Volume (vol) |
vol.120 |
Number (no) |
no.417 |
Page |
pp.12-17 |
#Pages |
6 |
Date of Issue |
2021-02-25 (LOIS) |
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