Feature detection in highly noisy images using random sample theory

2007 15th International Conference on Digital Signal Processing, DSP 2007

Volumn , Issue , 2007, Pages 423-426

  Gurbuz, Ali Cafer ^a   McClellan, James H ^a   Scott Jr , Waymond R ^a  

^a GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Fast line detection; Hough transform; RANSAC; Subsurface imaging

Indexed keywords

ALGORITHMS; BOOLEAN FUNCTIONS; DIGITAL SIGNAL PROCESSING; DIGITAL SIGNAL PROCESSORS; HOUGH TRANSFORMS; IMAGE ENHANCEMENT; MATHEMATICAL TRANSFORMATIONS; RANDOM PROCESSES; SIGNAL DETECTION; SIGNAL PROCESSING; STANDARDS;

3D (THREE DIMENSIONAL) IMAGING; CONVENTIONAL METHODS; DIGITAL SIGNALS; FEATURE DETECTION; FEATURE DETECTION ALGORITHMS; GPR IMAGING; GRAY-SCALE IMAGES; HOUGH TRANSFORM (HT); INTERNATIONAL CONFERENCES; LINEAR FEATURES; NOISY IMAGES; PERFORMANCE LEVEL (PL); RANDOM SAMPLES; SEARCH SPACES;

THREE DIMENSIONAL;

EID: 47649129017     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDSP.2007.4288609     Document Type: Conference Paper

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