7.图像梯度

Posted 2022-11-20 liuwenhua

#导入工具包

from imutils import *
image = imread(‘image/bricks.png‘)
show(image)

def gradient(image):
    image = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
    # cv2.CV_64F输出图像的深度(数据类型)，64位float类型，因为梯度可能是正也可能是负
    laplacian = cv2.Laplacian(image, cv2.CV_64F)
    # 1, 0表示在x方向求一阶导数，最大可以求2阶导数
    sobelx = cv2.Sobel(image, cv2.CV_64F, 1, 0, ksize=3)
    # 0, 1表示在y方向求一阶导数，最大可以求2阶导数
    sobely = cv2.Sobel(image, cv2.CV_64F, 0, 1, ksize=3)
    titles = [‘Original‘, ‘Laplacian‘, ‘SobelX‘, ‘SobelY‘]
    images = [image,laplacian,sobelx,sobely]
    plt.figure(figsize=(10,5))
    for i in range(4):
        plt.subplot(2,2,i+1)
        plt.imshow(images[i],‘gray‘)
        plt.title(titles[i])
        plt.axis(‘off‘)
    plt.show()

gradient(image)

image = imread(‘image/license_plate.png‘)
gradient(image)