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应用视觉注意多分辨率分析的图像检索

黄传波1, 金忠1(南京理工大学计算机科学与技术学院,南京 210094)

摘 要
基于人类视觉感知理论,提出一个改进的Itti视觉注意模型用于图像检索。该改进视觉注意模型是在充分考虑纹理特征与视觉感知关系的基础上,构造一个粗糙度图,用作视觉注意模型的一个初级视觉特征。首先通过该改进视觉注意模型得到50个视觉特征图;然后分别对每个视觉特征图采用局部二值模式傅里叶直方图(LBP-HF)方法抽取其分布信息,从而获得每幅图像的高维特征;最后利用局部保持投影(LPP)方法进行维数约简,以获取具有图像间局部几何和鉴别信息的低维特征用于图像检索。实验结果表明,该算法能获得较好的检索效果。
关键词
Image retrieval using multiresolution analysis of visual attention

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Abstract
In this paper,based on biologic visual information processing,an improved Itti’s visual attention model is proposed for image retrieval.By considering the relation between texture and visual perception,a coarseness map is constructed as a primary visual feature of the new visual attention model.Therefore,by the improved Itti’s model,we can obtain 50 feature maps,and extract the distributions information over the local binary pattern histogram fourier (LBP-HF) of each feature maps to get the high dimensional features.Finally,the locality preserving projections (LPP) is utilized for dimensionality reduction,and the low dimensional feature having both the local geometry and the discriminate information is used for image retrieval.Experimental results show that the proposed approach has good retrieval performance.
Keywords

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