基于多特征高效索引的图像检索

摘要

为了提高图像检索的准确率和速度，提出了一种多特征组合的图像检索算法。在颜色空间非均匀量化的基础上，利用改进的颜色聚合向量方法提取图像的颜色特征；基于改进的灰度共生矩阵提取纹理特征参数；利用Krawtchouk矩不变量提取图像的形状特征；基于贡献度聚类并建立特征索引库。融合上述特征计算图像间的相似度，使用特征索引对图像进行快速检索。实验结果表明，提出算法的检索精度有较大提高，能快速检索出用户所需的图像。%In order to improve the accuracy and speed of image retrieval, a method based on multi-features is presented in this paper. Based on the asymmetrical quantization of color space, improved color coherence vectors are used to extract the color feature;improved gray level co-occurrence matrix is utilized as the texture feature;Krawtchouk moment invari-ants are introduced to extract the shape feature; it is clustered based on the contribution and establishes image feature index library. The similarity between images is computed based on multi-features fusion, and image fast retrieval is obtain-able by using the feature index. Related experiments show that the retrieval precision of the proposed algorithm is improved greatly with faster retrieval speed.