基于广义图像灰度共生矩阵的图像检索方法

当图像发生旋转或大小改变显著时,用已有的基于灰度共生矩阵的图像检索方法,不能很好地给出检索结果,在此基础上,该文提出一种基于广义图像灰度共生矩阵的图像检索方法。该方法将原图像作平滑处理得到平滑图像,然后将原图像和平滑图像组合起来得到广义图像灰度共生矩阵,提取该矩阵的统计特征量后,将其组成向量并归一化后用于检索。该方法引入了图像的空间信息,对于图像旋转和尺寸变化均不敏感。实验结果与性能比较表明,新方法的效果优于单纯的灰度共生矩阵法。

Generalized Co-occurrence Matrix Method for Content-based Image Retrieval

The approach of co-occurrence matrix is widely used in texture-based image retrieval,yet it does not perform well when the image gets a rotation and great change in size.In this paper,the spatial information of the image is applied to image retrieval based on generalized image co-occurrence matrix.Firstly,a smoothed image is obtained by using Sobel operator.Secondly,we construct a matrix with the correspond pixels in both of these two images which is called generalized image co-occurrence matrix here.Thirdly,a set of statistical features according to this matrix is obtained.Finally,a vector composed with this set of statistical features is regarded as the final characterization of the image and is kept in the feature database.Experimental results show that the retrieval efficiency is improved greatly when being compared with the classic co-occurrence matrix method.