2021-01-07 python opencv image quality inspection: image brightness inspection

Python image quality detection: image brightness detection

Image quality detection based on traditional methods

Requirement : To
detect whether the video is abnormal in brightness, this code is used to detect a frame of pictures, and the video detection needs to be read by itself, and frame detection is performed according to requirements

Method :
By calculating the mean and variance on the grayscale image, when the brightness is abnormal, the mean will deviate from the mean point (it can be assumed to be 128), and the variance will be too small;

	# 把图片转换为单通道的灰度图
	gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
	
    # 获取形状以及长宽
    img_shape = gray_img.shape
    height, width = img_shape[0], img_shape[1]
    size = gray_img.size
    # 灰度图的直方图
    hist = cv2.calcHist([gray_img], [0], None, [256], [0, 256])

    # 计算灰度图像素点偏离均值(128)程序
    a = 0
    ma = 0
    reduce_matrix = np.full((height, width), 128)
    shift_value = gray_img - reduce_matrix
    shift_sum = sum(map(sum, shift_value))

    da = shift_sum / size

    # 计算偏离128的平均偏差
    for i in range(256):
        ma += (abs(i-128-da) * hist[i])
    m = abs(ma / size)
    # 亮度系数
    k = abs(da) / m
    # print(k)
    if k[0] > 1:
        # 过亮
        if da > 0:
            print("过亮")
        else:
            print("过暗")
    else:
        print("亮度正常")

The reference picture (you can use the picture inside to test) mainly depends on the brightness level: https://blog.csdn.net/weixin_41770169/article/details/82349687