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

机译:一种用于图像纹理分类的单纯形遗传混合方法

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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 quicldy, 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.
机译:本文提出了一种通过集成遗传算法和单纯形方法来对图像纹理进行分类的混合方法。 Simplex方法是一种通过反射,扩展和收缩操作获得新的和更好的单纯性点的本地搜索方法。由于该方法会聚Quicly,本文采用了Simplex方法的本地搜索特性,以避免遗传算法的早产。基于遗传算法的集成和单纯形方法,提出了一种混合算法来区分图像纹理。为了与遗传算法进行性能比较的目的,提出了五类空中图像的分类实验。实验结果表明,该方法是可行性,其性能优于遗传算法。

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