检测opencv中的黄色

Question

我将图像转换为HSV后,我将阈值设为黄色,因此代码为cvInRangeS(imgHSV,cvScalar(112,100,100),cvScalar(124,255,255),imgThreshed); 但它不起作用总是给我黑色的图像.

Answer 1

您应该尝试本教程"跟踪黄色对象".

它给出cvInRangeS(imgHSV, cvScalar(20, 100, 100), cvScalar(30, 255, 255), imgThreshed)黄色物体的HSV范围.

如果您对选择颜色有任何疑问,请尝试以下方法:http://www.yafla.com/yaflaColor/ColorRGBHSL.aspx

Answer 2

我知道你问的问题是针对 c++ 的，我有 python 脚本来检测黄色，这可能会帮助你或其他人。

def colorDetection(image):
    hsv = cv2.cvtColor(image,cv2.COLOR_BGR2HSV)

    '''Red'''
    # Range for lower red
    red_lower = np.array([0,120,70])
    red_upper = np.array([10,255,255])
    mask_red1 = cv2.inRange(hsv, red_lower, red_upper)

    # Range for upper range
    red_lower = np.array([170,120,70])
    red_upper = np.array([180,255,255])
    mask_red2 = cv2.inRange(hsv, red_lower, red_upper)

    mask_red = mask_red1 + mask_red2

    red_output = cv2.bitwise_and(image, image, mask=mask_red)

    red_ratio=(cv2.countNonZero(mask_red))/(image.size/3)

    print("Red in image", np.round(red_ratio*100, 2))



    '''yellow'''
    # Range for upper range
    yellow_lower = np.array([20, 100, 100])
    yellow_upper = np.array([30, 255, 255])
    mask_yellow = cv2.inRange(hsv, yellow_lower, yellow_upper)

    yellow_output = cv2.bitwise_and(image, image, mask=mask_yellow)

    yellow_ratio =(cv2.countNonZero(mask_yellow))/(image.size/3)

    print("Yellow in image", np.round(yellow_ratio*100, 2))