11 opencv python 圖像閾值

opencv python 圖像閾值¶

• cv2.THRESH_BINARY
• cv2.THRESH_BINARY_INV
• cv2.THRESH_TRUNC
• cv2.THRESH_TOZERO
• cv2.THRESH_TOZERO_INV

opencv 所有全局閾值格式¶

['THRESH_BINARY', 'THRESH_BINARY_INV', 'THRESH_MASK', 'THRESH_OTSU', 'THRESH_TOZERO', 'THRESH_TOZERO_INV', 'THRESH_TRIANGLE', 'THRESH_TRUNC']

import os
import matplotlib.pyplot as plt
import cv2

img = cv2.imread('huiDu.jpg', 0)

flag = [i for i in dir(cv2) if i.startswith('THRESH_')]
print(flag)

ret, thresh1 = cv2.threshold(img, 127, 255, cv2.THRESH_BINARY)
ret, thresh2 = cv2.threshold(img, 127, 255, cv2.THRESH_BINARY_INV)
ret, thresh3 = cv2.threshold(img, 127, 255, cv2.THRESH_TRUNC)
ret, thresh4 = cv2.threshold(img, 127, 255, cv2.THRESH_TOZERO)
ret, thresh5 = cv2.threshold(img, 127, 255, cv2.THRESH_TOZERO_INV)

titles = ['Original Image','BINARY','BINARY_INV','TRUNC','TOZERO','TOZERO_INV']
images = [img, thresh1, thresh2, thresh3, thresh4, thresh5]

fig = plt.figure(figsize=(80, 50))

for i in range(6):
    plt.subplot(3,2,i+1),plt.imshow(images[i],'gray')
    plt.title(titles[i], fontsize = 100)
    plt.xticks([]),plt.yticks([])

自適應閾值¶

• 此時的閾值是根據圖像上的每一個小區域計算與其對應的閾值。
• 因此在同一幅圖像上的不同區域採用的是不同的閾值，從而使我們能在亮度不同的情況下得到更好的結果。
• Block Size - 鄰域大小（用來計算閾值的區域大小）。
• C - 這就是是一個常數，閾值就等於的平均值或者加權平均值減去這個常數。

opencv 所有自適應閾值格式¶

['ADAPTIVE_THRESH_GAUSSIAN_C', 'ADAPTIVE_THRESH_MEAN_C']