我已經學習 CV 幾個月了，但是我在第二個專案中遇到了一個問題，我需要從一系列數字中去除噪音，以便應用 ocr。我設法清理它，但數字丟失了一些內部像素。
查看初始影像和當前最終影像。
uj5u.com熱心網友回復：
我設法解決了，我沒有使用你提到的方法，但這是一個好方法，我擔心它會導致字符膨脹，不利于OCR讀取。
這是我的最終結果：
for mrz in mrz_list:
try:
thresh = cv2.threshold(mrz, 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
dist = cv2.distanceTransform(thresh, cv2.DIST_L2, 5)
dist = cv2.normalize(dist, dist, 0, 1.0, cv2.NORM_MINMAX)
dist = (dist * 255).astype("uint8")
thresh = cv2.threshold(dist, 0, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3))
opening = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel)
cnts = cv2.findContours(opening.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = imutils.grab_contours(cnts)
chars = []
for c in cnts:
(x, y, w, h) = cv2.boundingRect(c)
if w >= 20 and h >= 25:
chars.append(c)
chars = np.vstack([chars[i] for i in range(0, len(chars))])
hull = cv2.convexHull(chars)
mask = np.zeros(mrz.shape[:2], dtype="uint8")
cv2.drawContours(mask, [hull], -1, 255, -1)
mask = cv2.dilate(mask, None, iterations=2)
final = cv2.bitwise_and(opening, opening, mask=mask)`
感謝大家。
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