Title: Reconfigurable computing architecture of fuzzy controller for vision enhancement in night surveillance robot

Authors: L. Maria Irudaya Leo Joseph; S. Rajarajan

Addresses: Department of Electronics and Communication Engineering, Sathyabama University, Chennai, Tamilnadu, India ' Department of Electronics and Communication Engineering, Sri Sai Ram Institute of Technology, Chennai, India

Abstract: Vision enhancement in night surveillance robot (FLC-VENSR) can be obtained by implementing an area efficient reconfigurable architecture of fuzzy logic comparator. The comparator contains a fuzzy logic algorithm for comparator design. The reconfigurable computing method will work very efficiently for images and videos captured under any sort of environment. The speed and area constraints can be met by quantifying the lessening in processing speed over and above FPGA resources that can be accomplished if a component of the image/video processing system is embedded onto a hardware depended platform like an FPGA. The proposed processor is executed and synthesised using Xilinx integrated software environment (ISE) and Spartan-3E XC3S5000E family. It is observed that the used area by the proposed processor is less compared to the available processor AFLC-PIDAM.

Keywords: FLC-VENSR; AFLC-PIDAM; 2D-LFSR; global histogram equalisation; GHE; anti-forensic; CURVELT.

DOI: 10.1504/IJBIDM.2017.086984

International Journal of Business Intelligence and Data Mining, 2017 Vol.12 No.4, pp.319 - 339

Received: 17 Oct 2016
Accepted: 03 Jan 2017
Published online: 03 Oct 2017 *

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