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Paper Abstract and Keywords
Presentation 2017-10-05 14:50
Segmentation of Campus Images based on Image Features for Building Recognition
Kenta Yamanishi, Shun Hattori, Yukinori Suzuki (Muroran-IT) IE2017-51
Abstract (in Japanese) (See Japanese page) 
(in English) We have been studying building recognition in natural images by taking picture in a college campus. Itis difficult to recognize buildings accurately because the campus image contains various objects other than buildings in a campus such as people, trees, grass, cars, bicycles and roads. We therefore carried out an image segmentation using image features for accurate building recognition. Two segmentation algorithms were examined: (1) supervised segmentation using Gabor features and a support vector machine and (2) unsupervised segmentation using statistical geometrical features. Segmentation was carried out after converting a color image to a gray scale image. An effective gray scale conversion for image segmentation was also investigated. Computational experiments showed that the supervised segmentation was not able to divide the test images (which were not used to train SVM) satisfactorily. On the other hand, the unsupervised segmentation was able to divide the test images roughly in both cases of luminance and MSB conversion, respectively.
Keyword (in Japanese) (See Japanese page) 
(in English) SGF / Gabor feature / image features / region segmentation / Gray scale conversion / SVM / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 228, IE2017-51, pp. 25-30, Oct. 2017.
Paper # IE2017-51 
Date of Issue 2017-09-28 (IE) 
ISSN Print edition: ISSN 0913-5685    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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Conference Information
Committee IE ITE-ME ITE-AIT  
Conference Date 2017-10-05 - 2017-10-06 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To IE 
Conference Code 2017-10-IE-ME-AIT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Segmentation of Campus Images based on Image Features for Building Recognition 
Sub Title (in English)  
Keyword(1) SGF  
Keyword(2) Gabor feature  
Keyword(3) image features  
Keyword(4) region segmentation  
Keyword(5) Gray scale conversion  
Keyword(6) SVM  
Keyword(7)  
Keyword(8)  
1st Author's Name Kenta Yamanishi  
1st Author's Affiliation Muroran Institute of Technology (Muroran-IT)
2nd Author's Name Shun Hattori  
2nd Author's Affiliation Muroran Institute of Technology (Muroran-IT)
3rd Author's Name Yukinori Suzuki  
3rd Author's Affiliation Muroran Institute of Technology (Muroran-IT)
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Speaker Author-1 
Date Time 2017-10-05 14:50:00 
Presentation Time 25 minutes 
Registration for IE 
Paper # IE2017-51 
Volume (vol) vol.117 
Number (no) no.228 
Page pp.25-30 
#Pages 6 
Date of Issue 2017-09-28 (IE) 

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