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Study on image feature selection: A genetic algorithm approach

机译:图像特征选择研究:一种遗传算法方法

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This study was mainly about genetic algorithms of feature selection. The features adopted by this paper include CCM and DBPSP for the relationship between color and texture, CHKM for the color information of an image. The genetic algorithm of this study is implemented by MatLab program. The genetic algorithm optimization and searching technology adopted mechanics of genes and natural selection, and the algorithm implementation steps are: population initialization, fitness functions, selection, crossover, mutation, iteration and evolution. Feature selections used here are Sequential Forward Selection (SFS), Sequential Backward Selection (SBS), and the genetic algorithm-based feature selection used in this essay respectively. This study was analyzed and compared the result of the experiment respectively. The experiment was carried out for comparing the image retrieval accuracy, feature selection and computing time of image retrieval.
机译:本研究主要是关于特征选择的遗传算法。本文采用的功能包括CCM和DBPSP,用于颜色和纹理之间的关系,CHKM为图像的颜色信息。本研究的遗传算法由Matlab程序实施。遗传算法优化和搜索技术采用基因和自然选择的机制,算法实施步骤是:人口初始化,健身功能,选择,交叉,突变,迭代和演化。这里使用的特征选择是分别在本文中使用的顺序前进选择(SFS),顺序后向选择(SBS)和基于遗传算法的特征选择。分析了该研究并分别与实验结果进行了比较。进行实验,用于比较图像检索精度,特征选择和图像检索计算时间。

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