Detecting generic low-level features in images

Traditional definitions of edges and corners are limited in the sense that they restrict their application. In this paper we generalize the concepts of edges and corners to 1D features and 2D features, respectively. The phase congruency theory is chosen as a mathematical system to model the generalized concepts. The basics of the phase congruency theory along with the local energy model are described. The extraction schemes of 2D features from 2D gray level images are studied and discussed as a demonstration of our generalization idea. The performance evaluation and the preliminary improvement show that this kind of generalization on features and the modeling are successful and promising