Scene classification using multiple features in a two-stage probabilistic classification framework

Neurocomputing

Volumn 73, Issue 16-18, 2010, Pages 2971-2979

  Sun, Zhan Li ^a   Rajan, Deepu ^b   Chia, Liang Tien ^b  

^a INSTITUTE OF INTELLIGENT MACHINES   (China)

^b NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Fourier transform; Gabor filter; Global feature; Gray level co occurrence matrix; Scene classification

Indexed keywords

CLASSIFICATION ACCURACY; CLASSIFICATION METHODS; CO-OCCURRENCE-MATRIX; DATA SETS; ENERGY FEATURE; FILTERED IMAGES; FREQUENCY DOMAINS; GABOR FILTER; GLOBAL FEATURE; GRAY LEVEL CO-OCCURRENCE MATRIX; HIGHER DIMENSIONS; LINEAR COMBINATIONS; MULTIPLE FEATURES; NATURAL SCENES; POSTERIOR PROBABILITY; PROBABILISTIC CLASSIFICATION; PROBABILISTIC OUTPUT; REAL SCENES; SCENE CLASSIFICATION; TEXTURAL CHARACTERISTIC; TWO STAGE;

CLASSIFICATION (OF INFORMATION); FOURIER TRANSFORMS; FREQUENCY DOMAIN ANALYSIS;

FEATURE EXTRACTION;

ACCURACY; ARTICLE; CLASSIFICATION; IMAGE DISPLAY; IMAGE INTENSIFIER; IMAGE PROCESSING; IMAGE RETRIEVAL; INTERMETHOD COMPARISON; METHODOLOGY; POWER SPECTRUM; PRIORITY JOURNAL; PROBABILITY; SCENE CLASSIFICATION; SUPPORT VECTOR MACHINE;

EID: 78650175082     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2010.07.004     Document Type: Article

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