A Monte Carlo algorithm for extracting contours in 2D images is proposed in this paper. A multiple model Particle Filter (PF) for progressive contour growing (tracking) from a starting point is designed, accounting for the convex, noncircular form of delineated areas. The algorithm relies on image intensity gradients as measurements and requires information about four manually selected points: the seed point, the starting point, arbitrarily selected on the contour, and two additional points, bounding the measurement formation area around the contour. The filter performance is studied by segmenting contours from series of simulated ultrasound medical images and Ground Penetrating Radar (GPR) images.