中文说明：这个项目得到了进一步的探索和视觉特征提取的研究。根据 HSV （色相、 饱和度值） 颜色空间，颜色的特征提取的工作完成的过程是，如下所示： 量化的色彩空间在非等间隔，构建一个维度特征向量和累积所代表的颜色特征直方图。同样，纹理特征提取的工作通过使用灰度共生矩阵 （灰度共生矩阵） 或色彩共生矩阵 （CCM）。通过 HSV 颜色空间的量化，我们结合颜色特征 和灰度共生矩阵，以及 CCM 分开。取决于前者，基于多特征融合的图像检索是通过采用归一化的欧氏距离分类器。通过图像检索实验表明，使用颜色特征和基于 CCM 的纹理具有明显的优势。
English Description：
This PROJECT has a further exploration and study of visual feature extraction. According to the HSV (Hue, Saturation, Value) color space, the work of color feature extraction is finished, the process is as follows: quantifying the color space in non-equal intervals, constructing one dimension feature vector and representing the color feature by cumulative histogram. Similarly, the work of texture feature extraction is obtained by using gray-level co-occurrence matrix (GLCM) or color co-occurrence matrix (CCM). Through the quantification of HSV color space, we combine color features and GLCM as well as CCM separately. Depending on the former, image retrieval based on multi-feature fusion is achieved by using normalized Euclidean distance classifier. Through the image retrieval experiment, indicate that the use of color features and texture based on CCM has obvious advantage.