Edge Characterization Using Normalized Edge Detector

Abstract

The behavior of the normalized gradient of the Gaussian edge operator is analyzed over many scales in one and two dimensions. A knowledge of the changes that occur over scale in the output of the operator and the physical conditions that cause these changes is essential for the proper interpretation and application of the results. The behavior of several edge models and combinations of edges is examined. As a result it is shown that the slope of an edge can be estimated very accurately using one small scale. By following the rate of change in the output of the operator as scale changes, an optimal scale can be determined for estimating the width and total contrast of the edge. Results on real images are shown and it is demonstrated that the information obtained by these methods can be used to characterize edge points.