Using centroid covariance in target recognition
Gang Liu, R.M. Haralick · 2002
An automatic target recognition algorithm for low quality imagery is reported. Compact shaped targets are represented by their 2D silhouettes. Associated with each point on the silhouette, there is a direction roughly perpendicular to the local segment of the silhouette. The location of each silhouette point is assumed to be perturbed along that direction. A statistical technique is used to estimate the variance of that perturbation for the silhouette points of the hypothesized target. This variance is then used to estimate the location covariance of the target centroid. Target detection and recognition is based on this covariance. Target scaling, aspect, and rotation are not considered. Experiments on 31 FLIR images give a correct recognition of target identity and target location for 29 of the 31 images.