Publication | Closed Access
Multi-level threshold selection based on artificial bee colony algorithm and maximum entropy for image segmentation
18
Citations
20
References
2012
Year
Search OptimizationImage AnalysisOptimal Image ThresholdsEngineeringPattern RecognitionFirefly AlgorithmArtificial BeeMaximum EntropyEdge DetectionImage SegmentationEntropy FunctionMulti-level Threshold Selection
Image threshold segmentation based on artificial bee colony algorithm (ABCA) and maximum entropy is presented in this paper. The entropy function is simplified with several parameters. The ABC is applied to search the maximum value of entropy function. According to the maximum function value, the optimal image thresholds are obtained. Experimental results are provided to demonstrate the superior performance of the proposed approach.
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