A Multiscanning Approach Based on Morphological Filtering

It is argued that the mathematical morphology method seems to be more reasonable and powerful in studying certain multiscaling vision problems than the approach that uses derivatives of Gaussian-shaped filters of different sizes. To show the validity of this method, the authors concentrated on an application that involves forming scale-space image of a 2-D shape using morphological opening filtering. A proof is given to show that morphological opening filtering has a property of not introducing additional zero-crossings as one moves to a coarser scale. This is a different result from the conclusion by A.L. Yuille and T.A. Poggio (ibid., vol.PAMI-8, Jan. 1986) that the Gaussian filter is the only filter with this property. In addition, opening filtering is computationaly simpler than the Gaussian filter. >

[1]  G. Matheron Random Sets and Integral Geometry , 1976 .

[2]  Jean Serra,et al.  Image Analysis and Mathematical Morphology , 1983 .

[3]  Alan L. Yuille,et al.  Scaling Theorems for Zero Crossings , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  J. Serra Introduction to mathematical morphology , 1986 .

[5]  Ioan Mackenzie James,et al.  General topology and homotopy theory , 1984 .

[6]  Andrew P. Witkin,et al.  Uniqueness of the Gaussian Kernel for Scale-Space Filtering , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  Farzin Mokhtarian,et al.  Scale-Based Description and Recognition of Planar Curves and Two-Dimensional Shapes , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.