Investigating Hidden Markov Models' Capabilities in 2D Shape Classification

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 26, Issue 2, 2004, Pages 218-286

  Bicego, Manuele ^a   Murino, Vittorio ^a  

^a UNIVERSITY OF VERONA   (Italy)

Author keywords

2D shape classification; Hidden Markov Models; Model selection; Probabilistic learning

Indexed keywords

ALGORITHMS; COMPUTER VISION; DATABASE SYSTEMS; ERROR ANALYSIS; FOURIER TRANSFORMS; IMAGE SEGMENTATION; LEARNING SYSTEMS; MATHEMATICAL MODELS; OBJECT RECOGNITION; PERTURBATION TECHNIQUES; PHASE SHIFT; PROBABILITY DISTRIBUTIONS; ROBUSTNESS (CONTROL SYSTEMS); ROTATION; SHEARING; TOPOLOGY;

HIDDEN MARKOV MODELS (HMM); MODEL SELECTION; PROBABILISTIC LEARNING; TWO-DIMENSIONAL SHAPE CLASSIFICATIONS;

MARKOV PROCESSES;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPARATIVE STUDY; COMPUTER ASSISTED DIAGNOSIS; COMPUTER GRAPHICS; COMPUTER SIMULATION; EVALUATION; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; INFORMATION RETRIEVAL; MATHEMATICAL COMPUTING; METHODOLOGY; PROBABILITY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING; STATISTICAL MODEL; VALIDATION STUDY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER GRAPHICS; COMPUTER SIMULATION; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFORMATION STORAGE AND RETRIEVAL; MARKOV CHAINS; MODELS, STATISTICAL; NUMERICAL ANALYSIS, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED; SUBTRACTION TECHNIQUE;

EID: 0742321098     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2004.1262200     Document Type: Article

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