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GPU Approach for Handwritten Devanagari Document Binarization

  • Sandhya Arora
  • Sunita Jahirabadkar
  • Anagha Kulkarni
Conference paper
First Online:
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 670)

Abstract

The optical character recognition (OCR) is the process of converting scanned images of machine printed or handwritten text, numerals, letters, and symbols into a computer processable format such as ASCII. For creating OCR’s paperless application, a system of high speed and of better accuracy is required. Parallelization of algorithm using graphics processing unit (GPU) along with CPU can be used to speed up the processing. In GPU computing, the compute-intensive operations are performed on GPU while serial code still runs on CPU. Binarization is one of the most fundamental preprocessing techniques in the area of image processing and pattern recognition. This paper proposes an adaptive threshold binarization algorithm for GPU. The aim of this research work is to speed up binarization process that eventually will help to accelerate the processing of document recognition. The algorithm implementation is done using Compute Unified Device Architecture (CUDA) software interface by NVIDIA. An average speedup of 2× is achieved on GPU GeForce 210 having 16 CUDA cores and 1.2 compute level, over the serial implementation.

Keywords

CUDA GPU OCR Binarization Parallelization Pattern recognition 
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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Sandhya Arora
    • 1
  • Sunita Jahirabadkar
    • 1
  • Anagha Kulkarni
    • 2
  1. 1.Department of Computer EngineeringCummins College of Engineering for WomenPuneIndia
  2. 2.IT DepartmentCummins College of Engineering for WomenPuneIndia

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