| IEICE Technical Committee Submission System Conference Paper's Information |
Online Proceedings [Sign in] Tech. Rep. Archives |
| Go Top Page | Go Previous | [Japanese] / [English] |
| Paper Abstract and Keywords | ||
| Presentation | 2023-03-02 14:40 QR code image dnoising netwroks based on decodability assessment Kazumitsu Takahashi, Makoto Nakashizuka (CIT)  SIS2022-46 |
|
| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In this paper, an image denoising method for QR code images is proposed. The image recovery from the degraded QR code image is performed to improve the successful rate of the data decoding from the QR code images. In many image recovery algorithms, which include image denoising, the objective of the algorithm is to decrease the mean square error between the clean image and the recovered image. However, the decrement of the mean square error is not related to improve the decoding rate directly. There exist any possible metric of the recovery that can improve the decoding rate. In this paper, the CNN (convolutional neural network) is applied to decodability assessment of the QR code and the trained network is employed to train the denosing network that improve the decoding rate of QR codes. In the proposed method, the CNN is trained to predict success or fail of decoding of the existing QR code decoder. The output of this CNN is defined as the decodability. Then, the denosing CNN is trained to minimize the loss function that consists of this decodability and the fidelity of the output image. In experiments, the decodability assessment of the CNN is demonstrated. We show that the decoding rate obtained from the denoising neural network that is trained with the decodability is superior to the denoising neural network trained with only mean square error. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | convolutional neural network / denoising / QR code / image recovery / decode / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 410, SIS2022-46, pp. 33-36, March 2023. | |
| Paper # | SIS2022-46 | |
| Date of Issue | 2023-02-23 (SIS) | |
| 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 | SIS2022-46 |
|
| Conference Information | |
| Committee | SIS |
| Conference Date | 2023-03-02 - 2023-03-03 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Chiba Institute of Technology |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | SIS |
| Conference Code | 2023-03-SIS |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | QR code image dnoising netwroks based on decodability assessment |
| Sub Title (in English) | |
| Keyword(1) | convolutional neural network |
| Keyword(2) | denoising |
| Keyword(3) | QR code |
| Keyword(4) | image recovery |
| Keyword(5) | decode |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Kazumitsu Takahashi |
| 1st Author's Affiliation | Chiba Institute of Technology (CIT) |
| 2nd Author's Name | Makoto Nakashizuka |
| 2nd Author's Affiliation | Chiba Institute of Technology (CIT) |
| 3rd Author's Name | |
| 3rd Author's Affiliation | () |
| 4th Author's Name | |
| 4th Author's Affiliation | () |
| 5th Author's Name | |
| 5th Author's Affiliation | () |
| 6th Author's Name | |
| 6th Author's Affiliation | () |
| 7th Author's Name | |
| 7th Author's Affiliation | () |
| 8th Author's Name | |
| 8th Author's Affiliation | () |
| 9th Author's Name | |
| 9th Author's Affiliation | () |
| 10th Author's Name | |
| 10th Author's Affiliation | () |
| 11th Author's Name | |
| 11th Author's Affiliation | () |
| 12th Author's Name | |
| 12th Author's Affiliation | () |
| 13th Author's Name | |
| 13th Author's Affiliation | () |
| 14th Author's Name | |
| 14th Author's Affiliation | () |
| 15th Author's Name | |
| 15th Author's Affiliation | () |
| 16th Author's Name | |
| 16th Author's Affiliation | () |
| 17th Author's Name | |
| 17th Author's Affiliation | () |
| 18th Author's Name | |
| 18th Author's Affiliation | () |
| Speaker | Author-1 |
| Date Time | 2023-03-02 14:40:00 |
| Presentation Time | 20 minutes |
| Registration for | SIS |
| Paper # | SIS2022-46 |
| Volume (vol) | vol.122 |
| Number (no) | no.410 |
| Page | pp.33-36 |
| #Pages | 4 |
| Date of Issue | 2023-02-23 (SIS) |
[Return to Top Page]