python - opencv:如何合并近轮廓以获得最大的轮廓？

Question

我正在尝试将 child 的绘图数字化为 SVG 或透明的 png 文件格式，以便它们可以在 Scratch 中使用。白纸应替换为透明背景，所有绘图部分应保留。

我的计划是获取绘图的最外轮廓并生成一个 mask ，然后使用 mask 来获取没有纸张背景的绘图部分。

问题是绘图可能不连续，这意味着可能有一些小孔导致将整个绘图轮廓分成许多小轮廓。

现在我想连接最近的最外轮廓以形成一个大的最外轮廓用于掩蔽。

附上原图和处理结果

代码:

from __future__ import print_function
import cv2 as cv
import numpy as np
import argparse
import random as rng
rng.seed(12345)
def thresh_callback(val):
    threshold = val
    # Detect edges using Canny
    canny_output = cv.Canny(src_gray, threshold, threshold * 2)
    # Find contours
    contours, hierarchy = cv.findContours(canny_output, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)
    # Draw contours
    drawing = np.zeros((canny_output.shape[0], canny_output.shape[1], 3), dtype=np.uint8)
    for i in range(len(contours)):
        color = (rng.randint(0,256), rng.randint(0,256), rng.randint(0,256))
        cv.drawContours(drawing, contours, i, color, 2, cv.LINE_8, hierarchy, 0)
    # Show in a window
    cv.imshow('Contours', drawing)
# Load source image
parser = argparse.ArgumentParser(description='Code for Finding contours in your image tutorial.')
parser.add_argument('--input', help='Path to input image.', default='IMG_4446.jpg')
args = parser.parse_args()
src = cv.imread(cv.samples.findFile(args.input))
if src is None:
    print('Could not open or find the image:', args.input)
    exit(0)
# Convert image to gray and blur it
src_gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
src_gray = cv.blur(src_gray, (3,3))
# Create Window
source_window = 'Source'
cv.namedWindow(source_window)
cv.imshow(source_window, src)
max_thresh = 255
thresh = 100 # initial threshold
cv.createTrackbar('Canny Thresh:', source_window, thresh, max_thresh, thresh_callback)
thresh_callback(thresh)
cv.waitKey()

Answer 1

import cv2, numpy as np

# Read Image
img = cv2.imread('/home/stephen/Desktop/test_img.png')
img  =cv2.resize(img, (750,1000))

# Find the gray image
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # Gray
gray = cv2.blur(gray, (2,2))
cv2.imwrite('/home/stephen/Desktop/gray.png',gray)

# Find the canny image
canny = cv2.Canny(gray, 30, 150) # Canny

# Find contours
contours, _ = cv2.findContours(canny,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)

# Draw contours on canny (this connects the contours)
cv2.drawContours(canny, contours, -1, 255, 6)
cv2.imwrite('/home/stephen/Desktop/contours.png',canny)

# Get mask for floodfill
h, w = canny.shape[:2]
mask = np.zeros((h+2, w+2), np.uint8)

# Floodfill from point (0, 0)
cv2.floodFill(canny, mask, (0,0), 123)
cv2.imwrite('/home/stephen/Desktop/floodfill.png',canny)

# Exclude everying but the floodfill region
canny = cv2.inRange(canny, 122, 124)
cv2.imwrite('/home/stephen/Desktop/inrange.png',canny)