An Embedded OCR: A Practical Case Study of Code Porting for a Mobile Platform

Author

Park, Jaehwa ; Kwon, Young-Bin

Author_Institution

Dept of Comput. Sci. & Eng., Chung-Ang Univ., Seoul, South Korea

fYear

2009

fDate

4-6 Nov. 2009

Firstpage

1

Lastpage

5

Abstract

Mobile platforms usually have highly versatile resources. To be a successful interface solution for mobile devices, OCR should have high computational efficiency and adaptation to platform diversity, which are usually trivial in a desktop system, in addition to good recognition rate. In this paper, a practical case study is presented, in which an OCR software is reformed from desktop to embedded version for mobile platforms. To reduce computational burden, all calculations are integerized and math functions are implemented in piecewise linear approximation. An idea of data structure for plug-in template is devised to enhance portability. A complete practical re-coding work has been done. In it a desktop version neural network based OCR is converted into an embedded style. The test results show 60% speed up without sacrificing the correct recognition rate, running on a half sized executable code.

Keywords

computational complexity; embedded systems; mobile computing; mobile handsets; neural nets; optical character recognition; piecewise linear techniques; OCR software; code porting; computational efficiency; data structure; embedded OCR; interface solution; mobile devices; mobile platform; neural network; piecewise linear approximation; platform diversity; plug-in template; recognition rate; Character recognition; Computational efficiency; Data preprocessing; Digital cameras; Image segmentation; Mobile computing; Neural networks; Optical character recognition software; Optical computing; Runtime;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 2009. CCPR 2009. Chinese Conference on

Conference_Location

Nanjing

Print_ISBN

978-1-4244-4199-0

Type

conf

DOI

10.1109/CCPR.2009.5343951

Filename

5343951