Hangul document image retrieval system using rank-based recognition

2005 ◽  
Author(s):  
Duk-Ryong Lee ◽  
Woo-Youn Kim ◽  
Il-Seok Oh
Keyword(s):  
Image Retrieval ◽  
Retrieval System ◽  
Document Image ◽  
Image Retrieval System

scholarly journals Face-based Document Image Retrieval System

2018 ◽  
Vol 132 ◽  
pp. 659-668 ◽  
Author(s):  
Umesh D. Dixit ◽  
M.S. Shirdhonkar
Keyword(s):  
Image Retrieval ◽  
Retrieval System ◽  
Document Image ◽  
Image Retrieval System

A Document Image Retrieval System

2010 ◽  
Vol 23 (6) ◽  
pp. 872-879 ◽  
Author(s):  
Konstantinos Zagoris ◽  
Kavallieratou Ergina ◽  
Nikos Papamarkos
Keyword(s):  
Image Retrieval ◽  
Retrieval System ◽  
Document Image ◽  
Image Retrieval System

A Duplicate Chinese Document Image Retrieval System

2005 ◽  
pp. 1-6
Author(s):  
Yung-Kuan Chan ◽  
Yu-An Ho ◽  
Hsien-Chu Wu ◽  
Yen-Ping Chu
Keyword(s):  
Image Retrieval ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Retrieval System ◽  
Word Processor ◽  
Document Image ◽  
Computer File ◽  
Image Retrieval System ◽  
Speed Up ◽  
Machine Readable

An optical character recognition (OCR) system enables a user to feed an article directly into an electronic computer file and translate the optically scanned bitmaps of text characters into machine-readable codes; that is, ASCII, Chinese GB, as well as Big5 codes, and then edits it by using a word processor. OCR is hence being employed by libraries to digitize and preserve their holdings. Billions of letters are sorted every day by OCR machines, which can considerably speed up mail delivery.

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