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Paper Abstract and Keywords
Presentation 2014-05-22 15:10
Window Size Estimation for Parametrically Describing Local Image Appearances by means of the Weighted Integral Method
Hidetoshi Goto, Hidekata Hontani (Nagoya Inst. of Tech.) SIP2014-9 IE2014-9 PRMU2014-9 MI2014-9
Abstract (in Japanese) (See Japanese page) 
(in English) The authors propose a new method that accurately estimates the parameters of the Gaussian function that describes a local appearance observed in each window at each location in given image. The Gaussian function is non-linear with respect to the parameters to be estimated, and the non-linearity makes the accurate parameter estimation difficult. In the proposed method, the weighted integral method is introduced to linearize the parameter estimation problem. The weighted integral method can estimate the parameters of the Gaussian functions that describe curvilinear structures. The estimated parameters, though, would be inaccurate if the local window includes more than one curvilinear structure. This means you need to adaptively select a window size that is appropriate for the estimation at each location in given images. In the proposed method, the window size is selected by evaluating the well-posedness of a system of the linear equations that the weighted integral method solves. Experimental results demonstrate that the proposed method estimates the parameters accurately with the appropriate size window.
Keyword (in Japanese) (See Japanese page) 
(in English) feature description / parameter estimation problem / scale analysis / weighted integral method / / / /  
Reference Info. IEICE Tech. Rep., vol. 114, no. 42, MI2014-9, pp. 43-48, May 2014.
Paper # MI2014-9 
Date of Issue 2014-05-15 (SIP, IE, PRMU, MI) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
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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 SIP2014-9 IE2014-9 PRMU2014-9 MI2014-9

Conference Information
Committee PRMU MI IE SIP  
Conference Date 2014-05-22 - 2014-05-23 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
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Paper Information
Registration To MI 
Conference Code 2014-05-PRMU-MI-IE-SIP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Window Size Estimation for Parametrically Describing Local Image Appearances by means of the Weighted Integral Method 
Sub Title (in English)  
Keyword(1) feature description  
Keyword(2) parameter estimation problem  
Keyword(3) scale analysis  
Keyword(4) weighted integral method  
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1st Author's Name Hidetoshi Goto  
1st Author's Affiliation Nagoya Institute of Technology (Nagoya Inst. of Tech.)
2nd Author's Name Hidekata Hontani  
2nd Author's Affiliation Nagoya Institute of Technology (Nagoya Inst. of Tech.)
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Speaker Author-1 
Date Time 2014-05-22 15:10:00 
Presentation Time 30 minutes 
Registration for MI 
Paper # SIP2014-9, IE2014-9, PRMU2014-9, MI2014-9 
Volume (vol) vol.114 
Number (no) no.39(SIP), no.40(IE), no.41(PRMU), no.42(MI) 
Page pp.43-48 
#Pages 6 
Date of Issue 2014-05-15 (SIP, IE, PRMU, MI) 

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