Neuromorphic acceleration for context aware text image recognition

Qinru Qiu, Zhe Li, Khadeer Ahmed, Hai Helen Li, Miao Hu

Research output: Chapter in Book/Entry/PoemConference contribution

4 Scopus citations


Although existing optical character recognition (OCR) tools can achieve excellent performance in text image detection and pattern recognition, they usually require a clean input image. Most of them do not perform well when the image is partially occluded or smudged. Humans are able to tolerate much worse image quality during reading because the perception errors can be corrected by the knowledge in word and sentence level context. In this paper, we present a brain-inspired information processing framework for context-aware Intelligent Text Recognition (ITR) and its acceleration using memristor based crossbar array. The ITRS has a bottom layer of massive parallel Brain-state-in-a-box (BSB) engines that give fuzzy pattern matching results and an upper layer of statistical inference based error correction. The framework works robustly in noisy environment. A parallel architecture is presented that incorporates the memristor crossbar array to accelerate the pattern matching. Compared to traditional microprocessor, the accelerator has the potential to provide tremendous area and power savings and more than 8,000 times speedups.

Original languageEnglish (US)
Title of host publicationIEEE Workshop on Signal Processing Systems, SiPS
Subtitle of host publicationDesign and Implementation
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479965885
StatePublished - Dec 15 2014
Event2014 IEEE Workshop on Signal Processing Systems, SiPS 2014 - Belfast, United Kingdom
Duration: Oct 20 2014Oct 22 2014

Publication series

NameIEEE Workshop on Signal Processing Systems, SiPS: Design and Implementation
ISSN (Print)1520-6130


Other2014 IEEE Workshop on Signal Processing Systems, SiPS 2014
Country/TerritoryUnited Kingdom


  • memristor crossbar array
  • neuromorphic
  • text recognition

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Signal Processing
  • Applied Mathematics
  • Hardware and Architecture


Dive into the research topics of 'Neuromorphic acceleration for context aware text image recognition'. Together they form a unique fingerprint.

Cite this