Optimization of Image Texture Features Based on Genetic Algorithms
Optimization of a set of texture features of firing process image is described. It is based on a genetic algorithm with elite selection. Optimization criterion is formulated. It is maximization of middle image segmentation accuracy when we find four fields: “torch”, “material”, “lining” and “carcass and burner”. Optimal combination of texture features is found. It includes four features: autocorrelation, homogeneity, intensity, variation. Software which implements the considered task is developed.