Jean-Francois Rivest, Pierre Soille, Serge Beucher
Journal of Electronic Imaging, Vol. 2, Issue 04, (October 1993) https://doi.org/10.1117/12.159642
TOPICS: Image segmentation, Edge detection, 3D image processing, Mathematical morphology, Electronic imaging, Composites, Sensors, Roads, 3D modeling, Image analysis
We survey the framework of morphological edge detection. Morphological gradients are hybrid operators: they are constructed with set and arithmetic operations. After a short introduction
to gradients in digital images, we present the gradients available in mathematical morphology: morphological gradients, half gradients, and directional gradients. These gradients are based on dilations and erosions. We present a new directional gradient based on graytone thinning/thickening and a new multiscale gradient called the regularized gradient. Morphological gradients have a considerable
advantage with respect to classical edge detection paradigms: they are easier to generalize to any type of space in which dilation can be defined. We describe the gradient operators in image sequences,
3-D images, and graphs. We propose a new operator on graphs, the mosaic gradient.