ICDAR 2021 Competition on Time-Quality Document Image Binarization

被引：17

作者：

Lins, Rafael Dueire ^{[1
,2
]}

Bernardino, Rodrigo Barros ^{[1
]}

Smith, Elisa Barney ^{[3
]}

Kavallieratou, Ergina ^{[4
]}

机构：

[1] Univ Fed Pernambuco, BR-50730120 Recife, PE, Brazil

[2] Univ Fed Rural Pernambuco, BR-52171900 Recife, PE, Brazil

[3] Boise State Univ, Boise, ID 83725 USA

[4] Univ Eagian, Mitilini, Greece

来源：

DOCUMENT ANALYSIS AND RECOGNITION, ICDAR 2021, PT IV | 2021年 / 12824卷

关键词：

Document binarization; DIB-dataset; Binarization competition; ALGORITHM; ENTROPY;

D O I：

10.1007/978-3-030-86337-1_47

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The ICDAR 2021 Time-Quality Binarization Competition assessed the performance of 12 new and 49 other previously published binarization algorithms for scanned document images. Four test sets of "real-world" documents with different features were used. For each test set, the top twenty algorithms in the quality of the resulting two-tone images had their average processing time presented, yielding an account of their time complexity.

引用

页码：708 / 722

页数：15

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