Abstract
In this paper we describe and compare two different approaches to design image processing algorithms for binary images using Genetic Programming (GP). The first approach is based on the use of mathematical morphology primitives. The second is based on Sub- Machine-Code GP: a technique to speed up and extend GP based on the idea of exploiting the internal parallelism of sequential CPUs. In both cases the objective is to find programs which can transform binary images of a certain kind into other binary images containing just a particular characteristic of interest. In particular, here we focus on the extraction of three different features in music sheets.
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Quintana, M.I., Poli, R., Claridge, E. (2003). On Two Approaches to Image Processing Algorithm Design for Binary Images Using GP. In: Cagnoni, S., et al. Applications of Evolutionary Computing. EvoWorkshops 2003. Lecture Notes in Computer Science, vol 2611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36605-9_39
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DOI: https://doi.org/10.1007/3-540-36605-9_39
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