中文摘要：

提出了一种高性能的图像检索方法，结合纹理分类和改进的Fisher向量实现图像检索。首先，将图像划分为互不重叠的图像子块，对每一图像子块依据纹理复杂度进行分类，对不同类别的图像子块提取不同的特征。其次，采用基于后验概率改进的Fisher向量进行特征编码，依据乘积量化和非对称距离计算方法，分段计算两特征向量之间的距离，快速求取相似度指标，据此进行图像检索。在Holidays数据集上进行图像检索的实验结果表明，该方法的查准率和召回率高，且耗费的查询时间少。

英文摘要：

An image retrieval method with high performance is proposed, which combing with texture classification and modified Fisher vector to realize image retrieval. First, the image is divided into non-overlapping image sub-blocks, each image sub-block is classified according to complexity of texture, and different features are extracted for different classes of image sub-blocks. Second, features are encoded by modified Fisher vector based on posterior probability, and the distance between two feature vectors is calculated segmentally according to product quantification and asymmetric distance calculation method, for rapid computing a similari- ty index and executing image retrieval. Experimental results for image retrieval on Holidays dataset show that, this method has high precision and recall, and less query time consuming.