PSO based parametric object recognition - Tan, Wooi-Haw; Besar, Rosli; Coatrieux, Gouenou; Solaiman, Basel (IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG, 2008)
In this paper, we propose an object recognition technique based on particle swarm optimization. Our technique reduces the complexity of the Hough transform and the rigidity of template matching via cross correlation, while harnessing the robustness of both methods. To demonstrate its effectiveness, the proposed technique has been applied for ellipsoid detection in three-dimensional images and satisfactory results have been obtained. The detected object is described by a set of parameters, which can be used for further processing. In addition, our technique can be adapted for the detection of other objects, provided that they can be represented by a set of parameters.