Boosting Optical Character Recognition: A Super-Resolution Approach

Autor:	Dong, Chao, Zhu, Ximei, Deng, Yubin, Loy, Chen Change, Qiao, Yu
Rok vydání:	2015
Předmět:	Computer Science - Computer Vision and Pattern Recognition I.4.3 I.4.9
Druh dokumentu:	Working Paper
Popis:	Text image super-resolution is a challenging yet open research problem in the computer vision community. In particular, low-resolution images hamper the performance of typical optical character recognition (OCR) systems. In this article, we summarize our entry to the ICDAR2015 Competition on Text Image Super-Resolution. Experiments are based on the provided ICDAR2015 TextSR dataset and the released Tesseract-OCR 3.02 system. We report that our winning entry of text image super-resolution framework has largely improved the OCR performance with low-resolution images used as input, reaching an OCR accuracy score of 77.19%, which is comparable with that of using the original high-resolution images 78.80%. Comment: 5 pages, 8 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1506.02211 Zobrazit plný text záznamu View this record from Arxiv