Texture Generation for Fashion Design Using Genetic Programming

We present a methodology to generate textures for fashion design using genetic programming (GP). The proposed GP based scheme evolves tree representation of procedures to generate textures. We use Contrast of the generated textures/images to filter out poor textures. After filtering, the fitness value of a new texture is set as the fitness value of a cluster of (already generated) textures which is more similar to this new texture. For this, we execute a clustering step during the evolution. Statistical features are used to find the similarity between textures. Since the quality of a texture is best assessed by a human being, if the generated texture is quite dissimilar to the existing textures then user´s discretion is sought to assign a fitness value to it by visual inspection of the texture