GPU-accelerated 2D OTSU and 2D entropy-based thresholding

  • Xianyi Zhu
  • Yi XiaoEmail author
  • Guanghua Tan
  • Shizhe Zhou
  • Chi-Sing Leung
  • Yan Zheng
Original Research Paper


Image thresholding methods are commonly used to distinguish foreground objects from a background. 2D thresholding methods consider both the value of a pixel and the mean of the pixel’s neighbors, so they are less sensitive to noises than 1D thresholding methods. However, the time complexity increases from \(O(\ell ^2)\) to \(O(\ell ^4)\), where \(\ell\) is the number of gray levels. This paper proposes a parallel algorithm (\(O(\ell + \ell \log \ell )\) ) to accelerate both 2D OTSU and 2D entropy-based thresholding on GPU. By dividing the thresholding methods into seven cascaded parallelizable computational steps, our algorithm performs all the computations on GPU and requires no data transfer between GPU memory and main memory. The time complexity analysis explains the theoretical superiority over the state-of-the-art CPU sequential algorithm (O( \(\ell ^2)\)). Experimental results show that our parallel thresholding runs 50 times faster than the sequential one without loss of accuracy.


2D OTSU thresholding 2D entropy-based thresholding GPU acceleration Image binarization 2D histogram generation 



The work is supported by the National Key R & D Program of China (2018YFB0203904), NSFC from PRC (61872137, 61502158, 61602165, 61303147), Hunan NSF (2017JJ3042, 2018JJ3074) and GRF from Hong Kong (Project Num.: CityU 11259516).


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Xianyi Zhu
    • 1
  • Yi Xiao
    • 1
    Email author
  • Guanghua Tan
    • 1
  • Shizhe Zhou
    • 1
  • Chi-Sing Leung
    • 2
  • Yan Zheng
    • 3
  1. 1.College of Computer Science and Electronic EngineeringHunan UniversityChangshaPeople’s Republic of China
  2. 2.Department of Electronic EngineeringCity University of Hong KongKowloon TongHong Kong
  3. 3.College of Electrical and Information EngineeringHunan UniversityChangshaPeople’s Republic of China

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