Post on 24-Sep-2020
transcript
Ant Algorithm for Image Edge Detection
Stefka Fidanova, Zlatolilya IlchevaInstitute of Information and CommunicationInstitute of Information and Communication
Technologies Bulgarian Academy of SciencesBulgarian Academy of Sciences
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Real Ants BehaviorReal Ants Behavior
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Ant Colony OptimizationAnt Colony OptimizationProcedure ACOProcedure ACOBegin
initialize the pheromonefwhile stopping criterion not satisfied do
position each ant on a starting noderepeat
for each ant dochose next node
end forend foruntil every ant has build a solutionupdate the pheromone
end whileend whileend
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Transition ProbabilityTransition Probability
tll djifijij )(
tallowedjift k
tallowedb ibib
jjkij k
)()(obPr )(
otherwise0
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Pheromone UpdatingPheromone Updating
ijijij ρ)(+ρττ 1
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Image Edge Detectiong gHeuristic Information
IV VIV ijc
ij maxV
,1,11,11,1 jijijijic IIIIV
1,1,1,11,1
,,,,
jijijiji
jjjj
IIII ,,,, jijijiji
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Image Edge DetectionImage Edge Detection
11 jiI 11 jiI 11 jiI
ijI1ijI 1ijIj
I I I11 jiI jiI 1 11 jiI
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Image Edge Detectiong gPheromone Updating
)(1 initijij ρ)(+ρττ
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Image Edge Detectiong gSolution Construction End
1lkjip 1,,, lkjip
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Image Edge Detectiong gAlgorithm End
n averT )( ijaverT )(
nn TT 1 TT10stefka@parallel.bas.bg
Experimental ResultspAlgorith Parameters
pheromoneinitial5.0 i itparameternevaporatio5.0
pheromoneinitial5.0
init
antsofnumber50A
iterationsmaximal100000001.0
n
iterationsmaximal1000n
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Image Edge DetectionImage Edge Detection
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Experimental ResultsExperimental Results
05.01 25.01
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Experimental ResultsExperimental Results
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Experimental ResultsExperimental Results
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Experimental ResultsExperimental Results
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Experimental ResultsExperimental Results
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Comparison with Other ACOComparison with Other ACO
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Comparison with WaveletComparison with Wavelet
Complexity)(Wevelet
ComplexityMNLO
)(ACO MNO 19stefka@parallel.bas.bg
Thank for Your AttentionThank for Your Attention
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