Parallel method for automatic shape determination via the evolution of morphological sequences

Abstract

A parallel evolutionary method for object shape determination is proposed by automatically generating morphological operator and operation sequences. Artificial individuals built up from binary morphological operators and operations undergo recombination and mutation processes for producing new generations. The normalized correlation between the generated shape and the corresponding input image region is calculated for fitness. This method requires no preliminary knowledge of the object shape and also no constraints are used for image background and smoothness. The parallel evolutionary approach provides a fast and directed search on large number of possible morphological sequences and the method can be applied on a wide range of images. The morphological operations are implemented by low level image processing steps and executed as parallel tasks by applying both data and algorithmic parallelization. As a concrete application, this method is utilized for the shape determination of skin objects in a system consisting of a camera device connected to a grid architecture of transputer nodes.