DocumentCode :
690576
Title :
Optical Character Recognition (OCR) Performance in Server-Based Mobile Environment
Author :
Mantoro, Teddy ; Sobri, Abdul Muis ; Usino, Wendi
Author_Institution :
FTI, Univ. of Budi Luhur, Jakarta, Indonesia
fYear :
2013
fDate :
23-24 Dec. 2013
Firstpage :
423
Lastpage :
428
Abstract :
There are several Optical Character Recognition (OCR) mobile applications on the market running on mobile devices, both android and iOS (iPhone, iPad, iPod) platforms. The limitations of mobile device processor hinder the possible execution of computationally intensive applications that need less time of process. This paper proposes a framework of Optical Character Recognition (OCR) on mobile device using server-based processing. Comparison methods proposed by this paper by conducting a series of tests using standalone and server-based OCR on mobile devices, and compare the results of the accuracy and time required for the entire OCR processing. Server-based mobile OCR obtains 5% higher character recognition accuracy than the standalone OCR and its format recognition accuracy is 99.8%. The framework tries to overcome the limitation of mobile device capability process, so the devices can do the computationally intensive application more quickly.
Keywords :
mobile computing; optical character recognition; Android; OCR mobile applications; character recognition accuracy; format recognition accuracy; iOS; iPad; iPhone; iPod; mobile device processor; optical character recognition; server-based OCR; server-based mobile environment; server-based processing; standalone OCR; Accuracy; Cameras; Character recognition; Mobile communication; Mobile handsets; Optical character recognition software; Servers; Optical Character Recognition; accuracy; image processing; mobile device;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computer Science Applications and Technologies (ACSAT), 2013 International Conference on
Conference_Location :
Kuching
Type :
conf
DOI :
10.1109/ACSAT.2013.89
Filename :
6836618
Link To Document :
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