Improving features subset selection using genetic algorithms for iris recognition

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5064 LNAI, Issue , 2008, Pages 292-304

  Roy, Kaushik ^a   Bhattacharya, Prabir ^a  

^a Concordia University ^*  (Canada)

Author keywords

Biometrics; Collarette area localization; Gaussian mixture model; Genetic algorithms

Indexed keywords

ALGORITHMS; BACKPROPAGATION; BIOMETRICS; COMMUNICATION CHANNELS (INFORMATION THEORY); EVOLUTIONARY ALGORITHMS; FEATURE EXTRACTION; GENETIC ALGORITHMS; IMAGE SEGMENTATION; MATHEMATICAL MODELS; NETWORK PROTOCOLS; OBJECT RECOGNITION; PATTERN RECOGNITION; SENSOR NETWORKS; TECHNICAL PRESENTATIONS; TRELLIS CODES;

ACCURATE; COLLARETTE AREA LOCALIZATION; DATASETS; FALSE ACCEPT RATES; FALSE REJECT RATES; FEATURE SELECTIONS; FEATURE SUBSET SELECTIONS; GAUSSIAN MIXTURE MODEL; GAUSSIAN MIXTURE MODELS; HIGH DIMENSIONS; IRIS DATUM; IRIS PATTERNS; IRIS RECOGNITIONS; IRRELEVANT FEATURES; MULTIPLE FEATURES; OPTIMAL FEATURES; PRACTICAL; RECOGNITION RATES; SECURITY ISSUES; SELECTION CRITERIONS; SUBSET SELECTIONS; SUBSET SIZES; TEXTURAL FEATURES; WEST VIRGINIA UNIVERSITIES;

NEURAL NETWORKS;

EID: 54249089347     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-69939-2_28     Document Type: Conference Paper

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