Paper Info
Title
Performance characterization and acceleration of Optical Character Recognition on handheld platforms
Abstract
Optical Character Recognition (OCR) converts images of handwritten or printed text captured by camera or scanner into editable text. OCR has seen limited adoption in mobile platforms due to the performance constraints of these systems. Intel® Atom™ processors have enabled general purpose applications to be executed on handheld devices. In this paper, we analyze a reference implementation of the OCR workload on a low power general purpose processor and identify the primary hotspot functions that incur a large fraction of the overall response time. We also present a detailed architectural characterization of the hotspot functions in terms of CPI, MPI, etc. We then implement and analyze several software/algorithmic optimizations such as i) Multi-threading, ii) image sampling for a hotspot function and Hi) miscellaneous code optimization. Our results show that up to 2X performance improvement in execution time of the application and almost 9X improvement for a hotspot can be achieved by using various software optimizations. We designed and implemented a hardware accelerator for one of the hotspots to further reduce the execution time and power. Overall, we believe our analysis provides a detailed understanding of the processing overheads for OCR running on a new class of low power compute platforms.
Year
DOI
Venue
2010
10.1109/IISWC.2010.5648852
IISWC
Keywords
Field
DocType
software optimization,image convertors,optimisation,execution time,mobile platform,mobile handsets,primary hotspot function,editable text,detailed understanding,miscellaneous code optimization,detailed architectural characterization,printed text,algorithmic optimizations,handheld platform,performance characterization,handheld device,multiprocessing systems,image sampling,cameras,overall response time,low power,hotspot function,handwritten character recognition,architectural characterization,optical character recognition,multithreading,intel® atom™ processor,text analysis,ocr workload,low power general purpose processor,image segmentation,layout,code optimization,image resolution,hardware accelerator,pixel,image recognition
Program optimization,Multithreading,Computer science,Parallel computing,Optical character recognition,Reference implementation,Mobile device,Software,Hardware acceleration,Computer hardware,Embedded system,Performance improvement
Conference
ISBN
Citations 
PageRank 
978-1-4244-9296-1
3
0.38
References 
Authors
2
9
Name
Order
Citations
PageRank
Sadagopan Srinivasan11207.87
Li Zhao260434.84
Lin Sun330.38
Zhen Fang4917.62
Peng Li54732.05
Tao Wang623823.70
Ravishankar Iyer772035.52
Ramesh Illikkal848133.98
Dong Liu9233.21