针对基于内容的彩色图像相似性检索问题，提出了一种新的相似性彩色图像检索方法，该方法既考虑了图像的颜色特征，也考虑了图像的空间信息特征，即在对HSV颜色模型进行特殊处理的基础上，将提取的色调不变量作为图像的颜色特征，同时设计了图像状态矩阵来描述图像的形状信息和空间位置信息。在进行图像间的相似性测量时，为了结合不同的子特征进行全局的相似性检索，还采用Guassian模型对不同子特征间的距离进行了归一化处理。用不同类型的图像对这种方法进行的试验结果表明，它用于图像的相似性检索是很有效的，并具有较高的检索效率。

The color histogram based image retrieval method is simple and invariant for translation and rotation of the images but losing the spatial information of the color. Recentlymanymethods, such as accumulative histogram, color correlograms, local color histogram, etc, are introduced to improve the color histogrammethod. In this paper, a new content-based color image retrieval method is proposed, in which both the color content and the shape feature of the image have been taken into account. Firstly, based on the special disposal on the HSV color space, an improved accumulative histogram of the hue is calculated as the color feature. To attain the spatial information, H-, S-, and V-component of the image are firstly divided inton×nblocks which are classified into 3 status, flatness, texture and edge status. Then each gray image is translated into a matrix composed of those 3 status values. After that the status matrix is transformed into 1-dimension status sequence, the transition probability matrix of the sequence is calculated as the image’s spatial distribution information. In matching the similarity of the images, the Guassian model is used to normalize the different sub-characters distance. Experiments with different kinds of images indicate that this method is great effective in image’s retrieval.