On-line Japanese character recognition system for visually disabled persons

1996 ◽  
Author(s):  
K. Kiyota ◽  
S. Yamamoto ◽  
N. Ezaki ◽  
T. Sakurai
Keyword(s):  
Character Recognition ◽  
Recognition System ◽  
Disabled Persons ◽  
Japanese Character ◽  
On Line ◽  
Visually Disabled

A STRUCTURAL APPROACH TO ON-LINE CHARACTER RECOGNITION: SYSTEM DESIGN AND APPLICATIONS

1991 ◽  
Vol 05 (01n02) ◽  
pp. 311-335 ◽  
Author(s):  
FATHALLAH NOUBOUD ◽  
RÉJEAN PLAMONDON
Keyword(s):  
Character Recognition ◽  
Computation Time ◽  
Experimental Tests ◽  
Recognition System ◽  
Structural Approach ◽  
Chain Code ◽  
String Comparison ◽  
Average Computation Time ◽  
On Line ◽  
A Chain

This paper presents a real-time constraint-free handprinted character recognition system based on a structural approach. After the preprocessing operation, a chain code is extracted to represent the character. The classification is based on the use of a processor dedicated to string comparison. The average computation time to recognize a character is about 0.07 seconds. During the learning step, the user can define any set of characters or symbols to be recognized by the system. Thus there are no constraints on the handprinting. The experimental tests show a high degree of accuracy (96%) for writer-dependent applications. Comparisons with other system and methods are discussed. We also present a comparison between the processor used in this system and the Wagner and Fischer algorithm. Finally, we describe some applications of the system.

scholarly journals A Survey on the Classifiers in On-line Handwritten Uyghur Character Recognition System

2016 ◽  
Vol 9 (3) ◽  
pp. 189-198 ◽  
Author(s):  
Wujiahemaiti Simayi ◽  
Mayire Ibrayim ◽  
Dilmurat Tursun ◽  
Askar Hamdulla
Keyword(s):  
Character Recognition ◽  
Recognition System ◽  
On Line

Printed Japanese Character Recognition Using Multiple Commercial OCRs

2004 ◽  
Vol 8 (2) ◽  
pp. 200-207 ◽  
Author(s):  
Hidetoshi Miyao ◽  
◽  
Yasuaki Nakano ◽  
Atsuhiko Tani ◽  
Hirosato Tabaru ◽  
...  
Keyword(s):  
Character Recognition ◽  
Document Images ◽  
Text Documents ◽  
Matching Algorithm ◽  
Majority Logic ◽  
Character String ◽  
Optical Character ◽  
Japanese Character ◽  
On Line ◽  
Standard Character

This paper proposes two algorithms for maintaining matching between lines and characters in text documents output by multiple commercial optical character readers (OCRs). (1) a line matching algorithm using dynamic programming (DP) matching and (2) a character matching algorithm using character string division and standard character strings. The paper proposes a method that introduces majority logic and reject processing in character recognition. To demonstrate the feasibility of the method, we conducted experiments on line matching recognition for 127 document images using five commercial OCRs. Results demonstrated that the method extracted character areas with more accuracy than a single OCR along with appropriate line matching. The proposed method enhanced recognition from 97.61% provided by a single OCR to 98.83% in experiments using the character matching algorithm and character recognition. This method is expected to be highly useful in correcting locations at which unwanted lines or characters occur or required lines or characters disappear.

Design and Realization of On-Line Uyghur Handwritten Character Collection System

2014 ◽  
Vol 989-994 ◽  
pp. 4742-4746
Author(s):  
Halmurat Dilmurat ◽  
Kurban Ubul
Keyword(s):  
Data Collection ◽  
Word Recognition ◽  
Character Recognition ◽  
Recognition System ◽  
Collection System ◽  
System A ◽  
Handwritten Character ◽  
On Line ◽  
Recognition Systems ◽  
Whole Systems

Data collection is the first step in handwritten character recognition systems, and the data quality collected effects the whole systems efficiency. As the necessary subsystem of on-line handwritten character/word recognition system, a Uyghur handwritten character collection system is designed and implemented with Visual C++ based on the nature of Uyghur handwriting. Uyghur handwritings is encoded by 8 direction tendency and stored in extension stroke file. And they are collected based on the content of Text Prompt File. From experimental results, it can be concluded that the handwriting collection system indicates its strong validity and efficiency during the collection of Uyghur handwriting.

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