A morphological signature transform for shape description

Sven Loncaric, Atam P. Dhawan
1993 Pattern Recognition  
A novel shape description method based on the Morphological Signature Transform (MST) is presented in this dissertation. The MST uses multiresolution morphological image processing by non-convex multiple structuring elements. A binary image which contains the object shape to bedescribed is represented by means of a multiresolution pyramid. The method is based on the successive morphological erosions of the input image at di erent resolutions by primary and rotated structuring elements. The
more » ... of successively eroded images are computed for each structuring element at each p yramid level. The obtained set of numbers is arranged into vectors, ordered, and used as a shape descriptor. Experimental results demonstrate that the method is robust against noise and invariant to translation, rotation, and scale change. A new method for the selection of the optimal structuring element is presented in the second part of dissertation. For a given class of shapes the optimal structuring element for MST method is selected by means of a genetic algorithm. The optimization criteria is formulated to enable a robust shape matching. Experiments have been performed on a class of model shapes. The proposed optimal shape description method is applied to the problem of shape matching which evolves in many object recognition applications. Here, an unknown object is matched to a set of
doi:10.1016/0031-3203(93)90004-g fatcat:tiuxvhtugvc4no6xbsr6ctmkju