FINDING AN ITERATED FUNCTION SYSTEMS BASED REPRESENTATION FOR COMPLEX VISUAL STRUCTURES USING AN EVOLUTIONARY ALGORITHM

摘要

This paper presents an approach to the IFS inverse problem based on evolutionary computations. Having a bitmap image, we look for a set of functions that can reproduce a good approximation of a given image. A method using a variable number of mappings is proposed. A number of different crossover operators is described and tested. The possibility of enriching evolutionary algorithms by a specific type mechanism characteristic for replication of influenza viruses is discussed. The genetic material of the influenza type A virus consists of eight separate segments. In some types of tasks, such a structure of a genome can be more adequate than representation that consists of one sequence only. If influenza virus strains infect the same cell, then their RNA segments can mix freely, producing progeny viruses which represents the reasortment mechanism. Furthermore, mistakes leading to new mutations are common. The structure of problems for which such viral reproduction mechanisms can be effective are analyzed. The paper ends with some experimental results showing the images we were able to generate with the proposed method. The preliminary experimental results suggest that the introduction of the reasortment operator results in achieving satisfactory images in a smaller number of generations.