14 November 1996 Evolution of gray-scale morphology structures for the extraction of medical objects
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Abstract
An evolutionary method for object shape extraction is proposed on the basis of utilizing gray-scale morphological structures. Artificial individuals built up from gray-scale morphological operators are mapped into 2D data representation structures. These operator series' are then manipulated for producing new generations. The normalized correlation between the filtering results and the contributed input image areas is calculated for fitness. The extracted objects are obtained by carrying out the filtering results and the contributed input image areas is calculated for fitness. The extracted objects are obtained by carrying out the filtering with the best fit operator series'. This method requires no preliminary knowledge of the object shape, also no constraints are used for image background and smoothness. The evolutionary approach provides a global and directed search on a large number of possible morphological operators and a method that can be applied on a wide range images. As a concrete application, the method is utilized for the shape extraction of speckles and other skin deformities. Ultraviolet and blue filtered images of a cameras device are used for input. In order to obtain a fast method, the algorithm is executed on a multiprocessor basis. Detecting the shape of skin objects originated from benign and malign skin deformities like speckles and melanomas has great medical and cosmetic importance as well.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Andrea Kutics, Andrea Kutics, } "Evolution of gray-scale morphology structures for the extraction of medical objects", Proc. SPIE 2847, Applications of Digital Image Processing XIX, (14 November 1996); doi: 10.1117/12.258473; https://doi.org/10.1117/12.258473
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