TY - GEN
T1 - Text Image Super Resolution Using Deep Attention Neural Network
AU - Liu, Yun
AU - Yano, Remina
AU - Watanabe, Hiroshi
AU - Suzuki, Takuya
AU - Chujoh, Takeshi
AU - Ikai, Tomohiro
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - In this paper, we propose a super-resolution method for text images to improve the accuracy of optical character recognition (OCR). The accuracy of OCR is closely related to the resolution of the image, and when OCR is applied to low resolution text images, satisfactory results are often not obtained. In the proposed method, we extract more representative feature information from text images by combining channel and spatial attention. Furthermore, we propose a new loss function called 'edge loss'. Experimental results show that the recognition accuracy of text images by our SR method is 5.87% higher than that of the original low-resolution images, and also higher than the results of BICUBIC and the baseline model.
AB - In this paper, we propose a super-resolution method for text images to improve the accuracy of optical character recognition (OCR). The accuracy of OCR is closely related to the resolution of the image, and when OCR is applied to low resolution text images, satisfactory results are often not obtained. In the proposed method, we extract more representative feature information from text images by combining channel and spatial attention. Furthermore, we propose a new loss function called 'edge loss'. Experimental results show that the recognition accuracy of text images by our SR method is 5.87% higher than that of the original low-resolution images, and also higher than the results of BICUBIC and the baseline model.
KW - Optical Character Recognition (OCR)
KW - attention
KW - convolutional neural network
KW - super resolution
KW - text image
UR - http://www.scopus.com/inward/record.url?scp=85123464621&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85123464621&partnerID=8YFLogxK
U2 - 10.1109/GCCE53005.2021.9621914
DO - 10.1109/GCCE53005.2021.9621914
M3 - Conference contribution
AN - SCOPUS:85123464621
T3 - 2021 IEEE 10th Global Conference on Consumer Electronics, GCCE 2021
SP - 280
EP - 282
BT - 2021 IEEE 10th Global Conference on Consumer Electronics, GCCE 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th IEEE Global Conference on Consumer Electronics, GCCE 2021
Y2 - 12 October 2021 through 15 October 2021
ER -