Edge Detection Based on Mathematical Morphology and Iterative Thresholding

Edge detection is a crucial and basic tool in image segmentation. The key of edge detection in gray image is to detect more edge details, reduce the noise impact to the largest degree, and threshold the edge image automatically. According to this, a novel edge detection method based on mathematic morphology and iterative thresholding is proposed in this paper. A modified morphological transform through regrouping the priorities of several morphological transforms based on contour structuring elements is realized first, and then an edge detector is defined by using the multi-scale operation of the modified morphological transform to detect the gray-scale edge map. Finally, a new iterative thresholding algorithm is applied to obtain the binary edge image. Comparative study with other morphological methods reveals its superiority over de-noising capacity, edge details protection and un-sensitivity to the shape of the structuring elements