A morphological edge detector for gray-level image thresholding

Abstract

A morphological edge detector for robust real time image segmentation is proposed in this paper. Different from traditional thresholding methods that determine the threshold based on image gray level distribution, our method derives the threshold from object boundary point gray values and the boundary points are detected in the image using the proposed morphological edge detector. Firstly, the morphological edge detector is applied to compute the image morphological gradients. Then from the resultant image morphological gradient histogram, the object boundary points can be selected, which have higher gradient values than those of points within the object and background. The threshold is finally determined from the object boundary point gray values. Thus noise points inside the object and background are avoided in threshold computation. Experimental results on currency image segmentation for real time printing quality inspection are rather encouraging. © Springer-Verlag Berlin Heidelberg 2005.