A fast recursive algorithm based on fuzzy 2-partition entropy approach for threshold selection

Neurocomputing

Volumn 74, Issue 17, 2011, Pages 3072-3078

  Tang, Yinggan ^a,b   Mu, Weiwei ^b   Zhang, Ying ^c   Zhang, Xuguang ^b  

^a BEIJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

^b YANSHAN UNIVERSITY   (China)

^c National Lighting Test Center   (China)

Author keywords

Entropy; Fuzzy c partition; Image segmentation; Recursive algorithm; Thresholding

Indexed keywords

ANT-COLONY OPTIMIZATION; COMPUTATION COMPLEXITY; ENTROPY APPROACH; ENTROPY METHODS; EXHAUSTIVE SEARCH ALGORITHMS; FAST RECURSIVE ALGORITHMS; FUZZY C-PARTITION; FUZZY C-PARTITIONS; OPTIMAL PARAMETER COMBINATIONS; PARAMETERIZED; PROCESSING TIME; REAL IMAGES; RECURSIVE ALGORITHMS; S-FUNCTION; THREE PARAMETERS; THRESHOLD SELECTION; THRESHOLDING;

ARTIFICIAL INTELLIGENCE; C (PROGRAMMING LANGUAGE); ENTROPY; GENETIC ALGORITHMS; IMAGE SEGMENTATION; PARTICLE SWARM OPTIMIZATION (PSO); RECURSIVE FUNCTIONS; SIMULATED ANNEALING;

MEMBERSHIP FUNCTIONS;

ALGORITHM; ARTICLE; COLONY OPTIMIZATION; ENTROPY; FUZZY 2 PARTITION ENTROPY; FUZZY SYSTEM; GENETIC ALGORITHM; IMAGE PROCESSING; MATHEMATICAL COMPUTING; PARTICLE SWARM OPTIMIZATION; PRIORITY JOURNAL; RECURSIVE ALGORITHM; SIMULATED ANNEALING;

EID: 80052917247     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2011.04.010     Document Type: Article

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