Segmentation by fusion of histogram-based K-means clusters in different color spaces

IEEE Transactions on Image Processing

Volumn 17, Issue 5, 2008, Pages 780-787

  Mignotte, Max ^a  

^a UNIVERSITÉ DE MONTRÉAL   (Canada)

Author keywords

Berkeley image database; Color spaces; Fusion of segmentations; K means clustering; Textured image segmentation

Indexed keywords

CLUSTER ANALYSIS; COMPUTER VISION; IMAGE FUSION;

BERKELEY IMAGE DATABASE; COLOR SPACES; K-MEANS CLUSTERING;

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CLUSTER ANALYSIS; COLOR; COLORIMETRY; COMPUTER ASSISTED DIAGNOSIS; COMPUTER GRAPHICS; EVALUATION; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; INFORMATION RETRIEVAL; MATHEMATICAL COMPUTING; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; COLOR; COLORIMETRY; COMPUTER GRAPHICS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFORMATION STORAGE AND RETRIEVAL; NUMERICAL ANALYSIS, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED; SUBTRACTION TECHNIQUE;

EID: 42649108403     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2008.920761     Document Type: Article

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