[CV] 이미지 기본세팅 8 (확장 - dilation, 침식 - erosion)

https://webnautes.tistory.com/1257

OpenCV Python 강좌 - 모폴로지 연산 (Morphological Operations)

을 먼저보고오는게 이해가 더 잘됨

1.  threshold 

경계면 구분을 원활하게 진행함

 

import cv2
import matplotlib.pyplot as plt
import numpy as np

image_path= "./data/a.png"

image = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
"""
230보다 큰 값은 모두 255로 설정되고 작은값은 0으로 (흰색으로 바뀜)
"""

_, mask = cv2.threshold(image, 230, 255, cv2.THRESH_BINARY_INV)

image_list = np.hstack([
    image,
    mask
])

plt.imshow(image_list, 'gray')
plt.show()

 

 

 

2. 확장 침식 실험 - 02

import cv2
import matplotlib.pyplot as plt
import numpy as np

image_path= "./data/a.png"

image = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
_, mask = cv2.threshold(image, 230, 255, cv2.THRESH_BINARY_INV)

                        
kernel = np.ones((3,3), np.uint8)
dilation = cv2.dilate(mask, kernel, iterations=2) # iterations 반복횟수
erosion = cv2.erode(mask, kernel)                     

image_list = np.hstack([
    image,
    mask,
    dilation,  # 팽창
    erosion   # 침식
])

plt.imshow(image_list, 'gray')
plt.title('org img to mask, dilation, erosion')
plt.show()

 

 

image_path= "./data/a.png"

image = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
_, mask = cv2.threshold(image, 230, 255, cv2.THRESH_BINARY_INV)

                        
kernel = np.ones((3,3), np.uint8)
dilation = cv2.dilate(mask, kernel, iterations=2) # iterations 반복횟수
erosion = cv2.erode(mask, kernel)
opening = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)
closing = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)

image_list = np.hstack([
    image,
    mask,
    dilation, 
    erosion,  
    opening,  
    closing
])

plt.imshow(image_list, 'gray')
plt.title('org img to mask, dilation, erosion, opening, closing')
plt.show()

 

3. 확장 침식 실험 - 03

 

image_path= "./data/a.png"

image = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
_, mask = cv2.threshold(image, 230, 255, cv2.THRESH_BINARY_INV)

                        
kernel = np.ones((3,3), np.uint8)
dilation = cv2.dilate(mask, kernel, iterations=2) # iterations 반복횟수
erosion = cv2.erode(mask, kernel)
opening = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)
closing = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)

mg = cv2.morphologyEx(mask, cv2.MORPH_GRADIENT, kernel)   # 팽창과 침식의 차  / 경계, 윤곽선, 테두리 등을 추출에 주로 쓰임
th = cv2.morphologyEx(mask, cv2.MORPH_TOPHAT, kernel)     #                 이미지의 밝은 영역에서 뚜렷한 경계를 강조

image_list = np.hstack([
    image,
    mask,
    dilation, 
    erosion,  
    opening,  
    closing
])

image_list_01 = np.hstack([
    mg,
    th
])

plt.imshow(image_list, 'gray')
plt.title('org img to mask, dilation, erosion, opening, closing')
plt.show()

plt.imshow(image_list_01, 'gray')
plt.title('org img to mg, th')
plt.show()