融合全局和局部描述的图像检索方法

摘要

With respect to two typical problems in CBIR such that Global feature is lack of spatial localization and local description should deal with the problem of image segmentation, an image retrieval method that combines the global color feature and local Gabor wavelet feature is presented The global feature description, namely MPEG-7 dominant color feature, is extracted from the entire image. The image is partitioned into 5 overlapping blocks, and then Gabor wavelet transforms are carried out on these blocks to extract the Gabor texture feature and color moments as the local feature description. An improved Hausdroff distance metric is proposed to compute the similarity using the local description, which can overcome low Retrial rate caused by image translation and rotation. Finally, the total similarity is obtained by fusing the global similarity and local similarity. The experimental results on the Corel database demonstrate the efficiency of the proposed CBIR method.%针对基于内容的图像检索中全局描述缺乏空间位置信息及局部描述面临图像分割的问题,提出了一种基于全局颜色特征和局部Gabor小波纹理特征的图像检索方法.在整幅图上提取MPEG-7主颜色描述算子作为全局描述.将图像划分为5个有重叠的子区域,提取Gabor纹理特征与颜色矩构成局部描述,提出了改进的豪斯多夫距离并将其应用在局部描述的整体匹配中,克服了因图像的平移、旋转而造成检索率低的问题.融合全局相似度和局部相似度获得最终相似度.基于Corel数据库的实验结果表明了该方法的有效性.