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Paper Abstract and Keywords
Presentation 2023-11-17 14:40
Diffusion-based Geometric Unwarping and Illumination Correction for Document Images
Sota Imahayashi, Guoqing Hao, Satoshi Iizuka, Kazuhiro Fukui (Univ. of Tsukuba) PRMU2023-36
Abstract (in Japanese) (See Japanese page) 
(in English) This study proposes a method to improve the visibility of document images by correcting distortions and re-illuminating them using a latent diffusion model. Document images often suffer from folds, tilt, and shadows. Such distortions and shadows significantly diminish image visibility, posing a challenge for optical character recognition (OCR) tasks. Recent methods using convolutional neural networks have attempted to correct distortions and re-illuminate, but image transformations involving geometric deformations are difficult, and it is still difficult to correct distortions and re-illuminate with high accuracy. In this study, we propose a method for correcting distortion and re-illumination of document images using a latent diffusion model to solve these problems. In the proposed method, a degraded image containing distortions and shadows is transformed from pixel space to latent space and concatenated with Gaussian noise. Then, the process of removing the noise is repeated by a denoising network to generate a latent representation with completely removed noise. Finally, the generated latent representation is converted to pixel space, and the output image is obtained after distortion correction and re-illumination. The diffusion model has high generative capacity and is trained by maximum likelihood estimation, allowing for the generation of a wide variety of data and stable training. It can also recover the remainder from partial information and conditionally control the generation, making it possible to generate images with distortion correction and re-illumination conditional on a degraded image. This method is expected to achieve high-quality results in a wide variety of real-world document images, and has a wide range of potential applications.
Keyword (in Japanese) (See Japanese page) 
(in English) Document images / Geometric unwarping / Illumination correction / Latent diffusion model / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 266, PRMU2023-36, pp. 113-118, Nov. 2023.
Paper # PRMU2023-36 
Date of Issue 2023-11-09 (PRMU) 
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)
Download PDF PRMU2023-36

Conference Information
Committee PRMU IPSJ-CVIM IPSJ-DCC IPSJ-CGVI  
Conference Date 2023-11-16 - 2023-11-17 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To PRMU 
Conference Code 2023-11-PRMU-CVIM-DCC-CGVI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Diffusion-based Geometric Unwarping and Illumination Correction for Document Images 
Sub Title (in English)  
Keyword(1) Document images  
Keyword(2) Geometric unwarping  
Keyword(3) Illumination correction  
Keyword(4) Latent diffusion model  
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1st Author's Name Sota Imahayashi  
1st Author's Affiliation University of Tsukuba (Univ. of Tsukuba)
2nd Author's Name Guoqing Hao  
2nd Author's Affiliation University of Tsukuba (Univ. of Tsukuba)
3rd Author's Name Satoshi Iizuka  
3rd Author's Affiliation University of Tsukuba (Univ. of Tsukuba)
4th Author's Name Kazuhiro Fukui  
4th Author's Affiliation University of Tsukuba (Univ. of Tsukuba)
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Speaker Author-1 
Date Time 2023-11-17 14:40:00 
Presentation Time 90 minutes 
Registration for PRMU 
Paper # PRMU2023-36 
Volume (vol) vol.123 
Number (no) no.266 
Page pp.113-118 
#Pages 6 
Date of Issue 2023-11-09 (PRMU) 

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