def color_moments(filename):
    img = cv2.imread(filename)  # 读一张彩色图片
    if img is None:
        return
    hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)  # RGB空间转换为HSV空间
    h, s, v = cv2.split(hsv)
    color_feature = []  # 初始化颜色特征
# 一阶矩（均值 mean）
    h_mean = np.mean(h)  # np.sum(h)/float(N)
    s_mean = np.mean(s)  # np.sum(s)/float(N)
    v_mean = np.mean(v)  # np.sum(v)/float(N)
    color_feature.extend([h_mean, s_mean, v_mean])  # 一阶矩放入特征数组
# 二阶矩 （标准差 std）
    h_std = np.std(h)  # np.sqrt(np.mean(abs(h - h.mean())**2))
    s_std = np.std(s)  # np.sqrt(np.mean(abs(s - s.mean())**2))
    v_std = np.std(v)  # np.sqrt(np.mean(abs(v - v.mean())**2))
    color_feature.extend([h_std, s_std, v_std])  # 二阶矩放入特征数组
# 三阶矩 （斜度 skewness）
    h_skewness = np.mean(abs(h - h.mean()) ** 3)
    s_skewness = np.mean(abs(s - s.mean()) ** 3)
    v_skewness = np.mean(abs(v - v.mean()) ** 3)
    h_thirdMoment = h_skewness ** (1. / 3)
    s_thirdMoment = s_skewness ** (1. / 3)
    v_thirdMoment = v_skewness ** (1. / 3)
    color_feature.extend([h_thirdMoment, s_thirdMoment, v_thirdMoment])  # 三阶矩放入特征数组

    return color_feature