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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
Unique Identification Number - IJEDR1404055Page Number(s) - 3718-3724Pubished in - Volume 2 | Issue 4 | Dec 2014DOI (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