在 Canny 边缘检测上应用自适应阈值

问题描述

我想在我的项目数据集中删除图像的模糊背景，并且我已经在 here 中使用 Canny 边缘检测获得了一个非常好的解决方案。我想对 Canny 的双阈值要求应用自适应阈值。感谢您对此的任何帮助。

imageNames = glob.glob(r"C:\Users\Bikir\Pictures\rTest\*.jpg")
count=0
for i in imageNames:        
 
    img = Image.open(i)
    img = np.array(img)    

    # grayscale
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

    # canny - I want this two values (0 and 150) to be adaptive in this case      
    canned = cv2.Canny(gray,150)

    # dilate to close holes in lines
    kernel = np.ones((3,3),np.uint8)
    mask = cv2.dilate(canned,kernel,iterations = 1);

    # find contours
    # Opencv 3.4,if using a different major version (4.0 or 2.0),remove the first underscore
    _,contours,_ = cv2.findContours(mask,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE);

    # find the biggest contour
    biggest_cntr = None;
    biggest_area = 0;
    for contour in contours:
        area = cv2.contourArea(contour);
        if area > biggest_area:
            biggest_area = area;
            biggest_cntr = contour;

    # draw contours
    crop_mask = np.zeros_like(mask);
    cv2.drawContours(crop_mask,[biggest_cntr],-1,(255),-1);

    # opening + median blur to smooth jaggies
    crop_mask = cv2.erode(crop_mask,iterations = 5);
    crop_mask = cv2.dilate(crop_mask,iterations = 5);
    crop_mask = cv2.medianBlur(crop_mask,21);

    # crop image
    crop = np.zeros_like(img);
    crop[crop_mask == 255] = img[crop_mask == 255];    

    img = im.fromarray(crop)
    img.save(r"C:\Users\Bikir\Pictures\removed\\"+str(count)+".jpg") 

    count+=1

解决方法

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