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Paper Abstract and Keywords
Presentation 2020-09-01 17:20
Study on automatic label masking method for plant specimen images using CTPN
Depeng Zhang, Yasuhiko Higaki, Yasuo Sugai (Chiba Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) In this study, the image processing required for registration of the Haginiwa plant specimen image database in c-arc. Since Haginiwa plant specimens include rare plant specimens, important information such as the collection site cannot be disclosed and must be masked. Up to now, we have been experimenting with a label position identification method that utilizes character recognition, but sufficient accuracy has not been obtained. In order to solve this problem, we consider an automatic image processing method based on deep learning. In this research, we use the text detection network CTPN, the text on the label was detected and the position of the label was tried, and this method obtained a valid result.
Keyword (in Japanese) (See Japanese page) 
(in English) Plant specimen image / Deep learning / Automatic masking / Text detection / CTPN / / /  
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Conference Information
Committee IEICE-LOIS IEICE-EMM IEICE-IE IEE-CMN ME IPSJ-AVM  
Conference Date 2020-09-01 - 2020-09-02 
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Place (in English) Online 
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Paper Information
Registration To IEICE-LOIS 
Conference Code 2020-09-LOIS-EMM-IE-CMN-ME-AVM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Study on automatic label masking method for plant specimen images using CTPN 
Sub Title (in English)  
Keyword(1) Plant specimen image  
Keyword(2) Deep learning  
Keyword(3) Automatic masking  
Keyword(4) Text detection  
Keyword(5) 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  
2nd Author's Affiliation Chiba University (Chiba Univ.)
3rd Author's Name Yasuo Sugai  
3rd Author's Affiliation Chiba University (Chiba Univ.)
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Speaker Author-1 
Date Time 2020-09-01 17:20:00 
Presentation Time 25 minutes 
Registration for IEICE-LOIS 
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Volume (vol) vol.44 
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