A multi-threshold segmentation approach based on artificial bee colony optimization

Applied Intelligence

Volumn 37, Issue 3, 2012, Pages 321-336

  Cuevas, Erik ^a   Sención, Felipe ^a   Zaldivar, Daniel ^a   Pérez Cisneros, Marco ^a   Sossa, Humberto ^b  

^a UNIVERSITY OF GUADALAJARA   (Mexico)

^b INSTITUTO POLITÉCNICO NACIONAL   (Mexico)

Author keywords

Artificial Bee Colony; Automatic thresholding; Image segmentation; Intelligent image processing

Indexed keywords

ABC ALGORITHMS; ABC METHOD; ARTIFICIAL BEE COLONIES; AUTOMATIC THRESHOLDING; COMPLEX OPTIMIZATION; EXPECTATION-MAXIMIZATION ALGORITHMS; EXPERIMENTAL COMPARISON; FAST CONVERGENCE; GAUSSIAN FUNCTIONS; GAUSSIAN MIXTURE MODEL; GRADIENT-BASED METHOD; INITIAL CONDITIONS; INTELLIGENT BEHAVIOR; INTELLIGENT IMAGE PROCESSING; LOW SENSITIVITY; MULTI-THRESHOLD SEGMENTATION; MULTIPLE IMAGE; SEGMENTATION ACCURACY; THRESHOLD POINT; THRESHOLD SELECTION;

EVOLUTIONARY ALGORITHMS; OPTIMIZATION;

IMAGE SEGMENTATION;

EID: 84868381657     PISSN: 0924669X     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10489-011-0330-z     Document Type: Article

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