基于粗糙粒模型的图像纹理识别和检索

传统的纹理识别方法大多是对图像频谱的研究，文中尝试以粒计算理论为基础，利用分层思想对图像的纹理特征进行识别。首先，通过引入粒的边缘和分层熵的概念，建立粗糙粒理论，构造粗糙粒度空间模型。然后，构建基于粒的边缘和分层熵的相似度计算方法，得出一种图像纹理识别方法。该方法不仅提高模型在图像纹理识别上的实用性，而且通过对识别和检索过程的同步进行简化纹理识别的计算过程。最后，仿真实验表明，该模型及所用到的相关方法是可行的，与其它方法相比，该方法识别和检索效果较好。

Image Texture Recognition and Retrieval Based on Rough Granular Model

Most of the traditional image texture recognition method focuses on spectrum.In this paper,the layering idea is used based on granular computing theory to recognized the image texture features.Firstly,the rough granular theory is presented and the rough granular space model is constructed by introducing the concept of granular edges and layered entropy.Secondly,a kind of similarity calculation method is established based on granular edges and layered entropy.Then,a method of image texture recognition is put forward.The proposed method improves the practicality of the model and simplifies the calculation of texture recognition by synchronous identification and retrieval.Finally,the simulation result show that the performance of image retrieval is improved.The validity of the proposed method is testified by the contrast with other methods.