ICDAR2015 Competition on Text Image Super-Resolution

被引：0

作者：

Peyrard, Clement ^{[1
]}

Baccouche, Moez ^{[1
]}

Mamalet, Franck ^{[2
]}

Garcia, Christophe ^{[3
]}

机构：

[1] Orange Labs, 4 Rue Clos Courtel, F-35510 Cesson Sevigne, France

[2] Spikenet Technol, F-31130 Balma, France

[3] Univ Lyon, INSA Lyon, LIRIS, CNRS UMR5205, F-69621 Villeurbanne, France

来源：

2015 13TH IAPR INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION (ICDAR) | 2015年

关键词：

DICTIONARIES;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents the first international competition on Text Image Super-Resolution (SR) and the ICDAR2015-TextSR dataset. We describe the core of the competition: interest, dataset generation and evaluation procedure, together with participating teams and their respective methods. The obtained results, along with baseline image upscaling schemes and state-of-the-art SR approaches are reported and commented. The main conclusion of this competition is that SR systems may improve OCR performances by up to 16.55 points in accuracy compared with bicubic interpolation for the proposed low resolution images.

引用

页码：1201 / 1205

页数：5

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