A Simplex-Genetic Hybrid Approach for the Classification of Image Textures

This paper proposes a hybrid approach to classify image textures by integrating genetic algorithms and the simplex method. The simplex method is a kind of local searching method that gets new and better simplex points by reflection, expansion and contraction operations. Since the method converges quickly, this paper employs the local search characteristic of the simplex method to avoid the premature of genetic algorithms. Based on the integration of genetic algorithms and the simplex method, a hybrid algorithm is proposed to discriminate image textures. The classification experiments on five classes of aerial images are presented for the purpose of the performance comparison with genetic algorithms. The experimental results show that the proposed method is feasibility and its performance is better than that of genetic algorithms