【摘要】 提出一种利用神经网络获取图像语义的算法。通过构建一个RBF神经网络,在图像的颜色、纹理、形状等低层视觉特征和高层语义特征之间建立映射关系。利用遗传算法训练RBF网络,获得RBF网络的隐节点个数、中心、宽度和连接权值等参数值,训练成功后的神经网络能够自动获取图像的语义。实验结果表明,该算法具有较好的基于语义的检索效果,体现了人对图像内容的理解,符合人的思维习惯。更多还原

【Abstract】 The paper proposes a new algorithm to obtain image semantic by neural network.By means of a designed RBF neural network,the paper establishes the mapping relationship between the low-level features such as color,texture and shape,and the high-level semantic.A new training method using genetic algorithm is presented,which can get all the parameters(such as quantity,centers,widths and connection weights of RBF neural network).The successfully-trained neural network can obtain image semantic automatically.Experimental results indicate that the proposed image retrieval algorithm is effective in characterizing image semantic.更多还原