A morphological model for automatic edge detection: comparison with ad-hoc hysteresis thresholding

In edge detection, the application of gradient operators and other derived operators is commonly used. In all cases, the result is a grey level image which needs to be binarised. In this paper, an automatic method of binarisation based on a morphological model of edges is proposed. To prove the robustness of this approach, a testing method has been developed. This method compares the performance of the new approach with two manual methods often used: the application of an optimal threshold value, and the application of the hysteresis method. The comparison is made very accurately by computing statistical criteria such as specificity, sensitivity, predictivity and the percentage of well classified edges. The set of test images is made up of synthetic images with different kinds of noise (uniform or Gaussian) and an increasing amount of edges. This approach was applied on medical images and common images as well. The results demonstrate its reliability