Detecting objects in image sequences using rule-based control in an active contour model

A method is presented for tracking object boundaries in sequential images using an active contour model, based on fuzzy reasoning rule-based control. Evolution of contour segments is controlled by separate processes based on whether the segment is judged to be inside, outside, or near the boundary o...

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Bibliographic Details
Published in:IEEE transactions on biomedical engineering 2003-06, Vol.50 (6), p.705-710
Main Authors: Chao Han, Kerwin, W.S., Hatsukami, T.S., Jenq-Neng Hwang, Chun Yuan
Format: Article
Language:English
Subjects:
Active contours
Algorithms
Biological and medical sciences
Carotid Arteries - anatomy & histology
Chaos
Computer vision
Fuzzy Logic
Fuzzy reasoning
Heart
Humans
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Image motion analysis
Image segmentation
Image sequences
Imaging, Three-Dimensional - methods
Knee - anatomy & histology
Magnetic Resonance Imaging - instrumentation
Magnetic Resonance Imaging - methods
Medical sciences
Models, Biological
Object detection
Pattern Recognition, Automated
Phantoms, Imaging
Radiology
Reproducibility of Results
Sensitivity and Specificity
Subtraction Technique
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Summary:A method is presented for tracking object boundaries in sequential images using an active contour model, based on fuzzy reasoning rule-based control. Evolution of contour segments is controlled by separate processes based on whether the segment is judged to be inside, outside, or near the boundary of the object, leading to robust boundary detection.
ISSN:0018-9294
1558-2531
DOI:10.1109/TBME.2003.812190