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Evaluation of Canny and Sobel Edge Detection Technique using Xilinx System Generator

Authors(2) :-Gagan Baraskar, Pooja Thakre

Edge detection is the first step in many computer vision applications. Edge detection of image significantly reduces the amount of data and filters out unwanted or insignificant information and gives the significant information in an image. This information is used in image processing to detect objects in which there are some problems like false edge detection, missing of low contrast boundaries, problems due to noise etc. The aim of this paper is to develop an edge detection which automatically detects edges of digital image. The complete design of sobel edge algorithm using sobel filter and canny edge detector algorithm followed by the Gaussian filtering and gradient filter is done on Xilinx System Generator (XSG).The complete design combines MATLAB, Simulink and XSG. The VHDL code is generated by using Xilinx system generator (XSG). Further the generated VHDL code is synthesize in Xilinx ISE Design Suit 13.1. The Edge Detection method has been verified successfully with no visually perceptualerrors in the resulted images and also comparing theboth filters with an individually performance is justified clearly with Practical and Theoretical
Gagan Baraskar, Pooja Thakre
XSG, Canny, Sobel, VHDL,Gaussian Filter
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Publication Details
  Published in : Volume 3 | Issue 2 | January-February 2017
  Date of Publication : 2017-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 53-56
Manuscript Number : NCAEAS2313
Publisher : Technoscience Academy
PRINT ISSN : 2395-6011
ONLINE ISSN : 2395-602X
Cite This Article :
Gagan Baraskar, Pooja Thakre, "Evaluation of Canny and Sobel Edge Detection Technique using Xilinx System Generator", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 3, Issue 2, pp.53-56, January-February-2017.
Journal URL : http://ijsrst.com/NCAEAS2313

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