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ISSN: 2321-9939 | ESTD Year: 2013

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Paper Title
Comparative Analysis of EDGE detection using Fuzzy set theory and Automata Theory with existing edge detection methods with CLA
  Mauhik Thakkar,  Prof. Pranav Lapsiwala

Edge is the boundary between an object and the background, and identifies the boundary between overlapping and non-over lapping objects. This means that if the edges in an image can be identified accurately, all of the objects can be located and basic properties such as area, perimeter, and shape can be measured. Here fuzzy logic based image processing is used for accurate and noise free edge detection and Cellular Learning Automata (CLA) is used for enhance the previously-detected edges with the help of the repeatable and neighborhood-considering nature of CLA. The different result of edge detection technique and enhanced by Cellular Learning Automata are compared with fuzzy edge detected and resulting edge is enhanced using CLA. In this paper, all the algorithms and result are prepared in MATLAB.

Keywords- Edge Detection, Fuzzy Logic, Learning Automata, Cellular Learning Automata
Publication Details
Unique Identification Number - IJEDR1404055
Page Number(s) - 3718-3724
Pubished in - Volume 2 | Issue 4 | Dec 2014
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Mauhik Thakkar,  Prof. Pranav Lapsiwala,   "Comparative Analysis of EDGE detection using Fuzzy set theory and Automata Theory with existing edge detection methods with CLA", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.2, Issue 4, pp.3718-3724, Dec 2014, Available at :http://www.ijedr.org/papers/IJEDR1404055.pdf
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