传统的灰度共生矩阵是一种有效的纹理图像分析方法，它在图像理解和计算机视觉研究领域已得到了广泛的应用。为了更有效地进行图像检索，提出了一种新型的共生矩阵描述子，它是通过描述4个像素的空间相关性来进行图像检索。利用该共生矩阵描述子进行图像检索时，首先在RGB颜色空间中计算彩色梯度, 然后利用四像素共生矩阵来描述图像特征，并用于基于内容的图像检索。实验结果表明，四像素共生矩阵描述子能够结合颜色、纹理和形状特征，因此检索性能优于灰度共生矩阵和颜色相关图。

The traditional co occurrence matrix is an effective approach in texture image analysis. It is widely used in the research sense of image comprehension and computer vision. In order to improve the performance of image retrieval, a new kind of co occurrence matrix descriptor are introduced as novel features for image retrieval. It can describes the spatial correlation of four pixels. During the course of image retrieval using the co occurrence matrix descriptor, color gradient is computed from the RGB color space, then describe the image characteristic by four pixels co occurrence matrix and use to image retrieval is described. Experimental results have shown that four pixels co occurrence matrix descriptor can combine color, texture and shape characteristic, the performances are better than that of gray level co occurrence matrices and color correlograms.