Multithreshold segmentation based on artificial immune systems

Mathematical Problems in Engineering

Volumn 2012, Issue , 2012, Pages

  Cuevas, Erik ^a   Osuna Enciso, Valentin ^b   Zaldivar, Daniel ^a   Pérez Cisneros, Marco ^a   Sossa, Humberto ^b  

^a UNIVERSITY OF GUADALAJARA   (Mexico)

^b INSTITUTO POLITÉCNICO NACIONAL   (Mexico)

Author keywords

[No Author keywords available]

Indexed keywords

1D-HISTOGRAMS; ARTIFICIAL IMMUNE SYSTEM; BIO-INSPIRED COMPUTING; CLONAL SELECTION PRINCIPLE; CRITICAL STEPS; EXPECTATION-MAXIMIZATION ALGORITHMS; EXPERIMENTAL EVIDENCE; FAST CONVERGENCE; GAUSSIAN FUNCTIONS; GAUSSIAN MIXTURE MODEL; GRADIENT-BASED METHOD; HUMAN IMMUNE SYSTEMS; INITIAL CONDITIONS; LOW SENSITIVITY; MULTI-THRESHOLD SEGMENTATION; MULTITHRESHOLD; SELECTION ALGORITHM; SELECTION BASED; SHAPE DETECTION; THRESHOLDING;

COMPUTER VISION; IMAGE SEGMENTATION; OPTIMIZATION;

ALGORITHMS;

EID: 84864917846     PISSN: 1024123X     EISSN: 15635147     Source Type: Journal    
DOI: 10.1155/2012/874761     Document Type: Article

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