基于纹理的图像检索算法

基于图像内容的检索CBIR(content-based image retrieval)是近年来的一个研究热点。它能够帮助人们在庞大的数字图像库中准确、快速地找出需要的资料。从图像的纹理特征入手,以彩色纹理图像作为研究对象,提出了一种新的基于纹理的图像检索算法。算法以小波分析作为预处理,合理分析、设计了特征向量的构成,并根据这些特征进行相似度计算,从而得出分类结果。在实验中对100幅图像进行检索,检索结果的正确率为75%。为了进一步验证算法的鲁棒性,对35种纹理及其旋转180°的图像共70幅图像进行检索,正确识别率为64%。实验说明本算法具有较高的识别率,并具有一定的鲁棒性。与其它算法相比,本算法在具有较高识别率的同时,能反映近似纹理的聚类性,且本算法不要求图像的尺寸完全相同。

A New Image Retrieval Algorithm Based On Texture

The content-based image retrieval is an important research point in recent years.It can help finding images from the database exactly and quickly.Based on the image texture,this paper presents a new classification algorithm in which the wavelet analysis is performed,after the careful analysis,designs the features reasonably.Then,according to these features,the similarities of the textures are computed and the classification result is obtained.In the experiment,100 images are searched and 75% of the results are correct.In order to further prove the robustness of the algorithm,35 kinds of texture images are rotated to get 35 new images,then these 70 images are searched,the correct rate is 64%.The experiments show that the algorithm is effective and most of the textures can be correctly recognized by using it.Compared with other algorithms,it not only has high correct rate,but also is robust with respect to the results of the rotated images.According to the analysis of the distance between different textures,the algorithm could reflect the similarity of similar textures and meanwhile,does not necessarily require that the images are completely the same in size.