A New Exponential Function Based Method for Detecting Edges in Images
Yang Chen · 2010
Edges in images are considered to be basic low-level features in image processing and pattern recognition. In this paper, we propose a new method for edge detection using the exponential function. The pixel values within a mask are normalized so that they can be regarded as probabilities. Then, the sum of the exponential or the reciprocal of exponential functions of the probabilities is calculated. A threshold is chosen for generating the black and white edge image. Morphological operation is applied as post processing for refining the edges. The method is also extended to the case of color images. Simulation results show that the new method provides competitive performance compared with the Sobel and Canny methods. In addition, it is shown that the proposed method yields nearly identical effect as the entropy method with less computation time.