Paper
23 March 1994 Noise tolerant elastic matching model
Fu-Fa Chen, John J. Murray
Author Affiliations +
Proceedings Volume 2182, Image and Video Processing II; (1994) https://doi.org/10.1117/12.171069
Event: IS&T/SPIE 1994 International Symposium on Electronic Imaging: Science and Technology, 1994, San Jose, CA, United States
Abstract
This paper addresses the regional boundary extraction problem, which attempts to match a reference template contour to a desired target boundary in the presence of noise. A three-step iterative strategy is used: first, a local correspondence is set up between each pixel of the reference template and the target boundary; second, shape information is used to minimize the error from the first step; and third, the template contour is updated. The first step assigns a target pixel to each pixel of the template contour, using an iterated max-min estimator which gives the upper bound for the mean square error. The second step minimizes error by using correlation information between the template pixels; the correlation is approximated as a Gaussian weighted distance function, and effectively smoothes the template contour deformation from the first step. The third step uses this smoothed deformation to update the template contour, which then becomes the starting point for the next iteration. Experimental results are shown in which the algorithm is applied to medical NMR images and performance is compared to the SNAKE algorithm.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Fu-Fa Chen and John J. Murray "Noise tolerant elastic matching model", Proc. SPIE 2182, Image and Video Processing II, (23 March 1994); https://doi.org/10.1117/12.171069
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Error analysis

Detection and tracking algorithms

Palladium

Electroluminescence

Video processing

Brain

Neuroimaging

Back to Top