Volume 9 Number 2(Dec. 2017)
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IJCEE 2017 Vol.9(2): 403-420 ISSN: 1793-8163
DOI: 10.17706/IJCEE.2017.9.2.403-420

A New Lightweight and High Fault Tolerance Sobel Edge Detection Using Stochastic Computing

Ming Ming Wong, Dennis M. L. D. Wong, Cishen Zhang, and Ismat Hijazin
Abstract— A new Stochastic Computing (SC) circuit design paradigm for image processing system is presented in this work. Two improved SC computational functions are derived, which are namely the stochastic scaled addition and stochastic absolute value of difference. Data correlation is also incorporated in the design for effective circuit size reduction without imposing accuracy degradation in the hardware implementations. The proposed SC functions are next employed to design the new and lightweight Sobel edge detection. Experimental results obtained from detailed test analysis have proven that new implementation has satisfactory accuracy level and higher fault tolerance capability in comparison with their conventional counterparts. The works proposed are also implemented on an Altera Cyclone V 5CGXFC7D6F31C6 FPGA for hardware complexity evaluation.

Index Terms—Stochastic computing, scaled addition, absolute value of difference, Sobel edge detection, fault tolerance.

Ming Ming Wong is with Faculty of Engineering, Computing and Science, Swinburne University of Technology Sarawak, Malaysia.
Dennis M. L. D. Wong is with Heriot Watt University Malaysia, Wilayah Persekutuan Putrajaya, Malaysia.
Cishen Zhang and Ismat Hijazin are with Faculty of Science, Engineering and Technology, Swinburne University of Technology, Hawthorn, Australia.

Cite:Ming Ming Wong, Dennis M. L. D. Wong, Cishen Zhang, and Ismat Hijazin, "A New Lightweight and High Fault Tolerance Sobel Edge Detection Using Stochastic Computing," International Journal of Computer and Electrical Engineering vol. 9, no. 2, pp. 403-420, 2017.

General Information

ISSN: 1793-8163
Frequency: Semiyearly
Editor-in-Chief: Prof. Yucong Duan
Abstracting/ Indexing: EI (INSPEC, IET), Ulrich's Periodicals Directory, Google Scholar, EBSCO, Engineering & Technology Digital Library, ProQuest, and Electronic Journals Library
E-mail: ijcee@iap.org

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