Applying SIMD to optical character recognition (OCR)

Guan Yu; Gauthier Lafruit; Richard Stahl; Henk Corporaal; Peter Schelkens

doi:10.1117/12.783828

6 May 2008 Applying SIMD to optical character recognition (OCR)

Guan Yu, Gauthier Lafruit, Richard Stahl, Henk Corporaal, Peter Schelkens

Proceedings Volume 7000, Optical and Digital Image Processing; 70001F (2008) https://doi.org/10.1117/12.783828
Event: SPIE Photonics Europe, 2008, Strasbourg, France

Abstract

Optical Character Recognition (OCR) techniques are widely used in data/text entry, process automation. Decades of research efforts have made the accurate recognition of typewritten text largely accepted as a solved problem. Driven by practical usage demands, the low complexity and high performance implementation techniques of OCR systems are studied. Recent research shows that it may not be possible even for a simple OCR to run on a portable device without a specialized digital signal processor. In this paper, we present a highly data-parallelized implementation of OCR for typewritten text onto the linear processor array of the Xetal chip. Besides the preprocessing stage, the most computation intensive part of OCR recognizing individual characters is highly parallelized onto the Single Instruction Multiple Data (SIMD) engine of the Xetal chip, which can process a VGA-resolution text frame within one tenth of a second. In addition, different parallelization schemes are explored to make trade-off between the degree of parallelism and the costs of preprocessing to reorganize data to feed the SIMD engine and post-processing to assemble and collect results. The exploration of parallelized OCR application brings additional performance gain when mapped onto the linear processor array of the Xetal chip.

Citation Download Citation

Guan Yu, Gauthier Lafruit, Richard Stahl, Henk Corporaal, and Peter Schelkens "Applying SIMD to optical character recognition (OCR)", Proc. SPIE 7000, Optical and Digital Image Processing, 70001F (6 May 2008); https://doi.org/10.1117/12.783828

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available