O. Germain et P. Refregier, OPTIMAL SNAKE-BASED SEGMENTATION OF A RANDOM LUMINANCE TARGET ON A SPATIALLY DISJOINT BACKGROUND, Optics letters, 21(22), 1996, pp. 1845-1847
We describe a segmentation processor that is optimal for tracking the
shape of a target with random white Gaussian intensity appearing on a
random white Gaussian spatially disjoint background. This algorithm, b
ased on an active contours model (snakes), consists of correlations of
binary reference's with preprocessed versions of the scene image. Thi
s result can provide a practical method to adapt the reference image t
o correlation techniques. (C) 1996 Optical Society of America