A knowledge-based hierarchical method for detecting regions of interests (ROIs) uses prior knowledge of the targets and the image resolution in detecting ROIs. The result produces ROIs that contain only one target that is completely enclosed within the ROI. The detected ROI can conform to the shape of the target even if the target is of irregular shape. Furthermore, the method works well with images that contain connected targets or targets broken into pieces. The method is not sensitive to contrast levels and is robust to noise. Thus, this method effectively detects ROIs in common real world imagery that has a low resolution without costly processing while providing fast and robust results.