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中文摘要：
为了有效地提取图像特征以提高图像检索性能，借鉴生物视觉信息处理过程中的提取图像特征，提出一种结合视觉感知与局部二值模式（LBP）傅里叶直方图的图像检索算法．首先根据视觉感知特点，用主分量图作为亮度初级视觉特征，将形状边缘信息融入视觉注意模型，获得改进的Itti视觉注意模型，并基于该改进视觉注意模型得到50个视觉特征图；然后计算每个特征图的LBP傅里叶直方图特征，并将其结合在一起作为图像特征；最后利用局部保持投影（LPP）进行维数约简，获取低维特征用于图像检索．实验结果表明，该算法具有颜色、纹理及形状鉴别能力，能获得较好的检索效果．
英文摘要：
Inspired by the feature extraction during the biologic visual information processing, an algorithm based on a combination of visual perception and local binary pattern histogram Fourier （LBP-HF） is proposed to effectively extract the features to improve the performance of image retrieval. Firstly, principal component map is used as the primary visual feature of intensity. The information of shape and edge is further fused to improve the Itti＇s model. Therefore, we can obtain 50 feature maps. Secondly, the LBP-HF of each feature maps is computed and concatenated to get an enhanced image feature descriptor vector. Thirdly, the locality preserving projections （LPP） is utilized for dimensionality reduction, and the final low dimensional feature is used for image retrieval. The experimental results show that our method has the discrimination power against color, texture and shape features and has good retrieval performance.
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