查找由两部分组成的字母的轮廓

Question

假设我有一个字母图像，我想找到这些字母的区域。

我写了这段代码：

MIN_CONTOUR_AREA = 10   
img = cv2.imread("alphabets.png")     
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)    
blured = cv2.blur(gray, (5,5), 0)    
img_thresh = cv2.adaptiveThreshold(blured, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV, 11, 2)
imgContours, Contours, Hierarchy = cv2.findContours(img_thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
for contour in Contours:
    if cv2.contourArea(contour) > MIN_CONTOUR_AREA:
        [X, Y, W, H] = cv2.boundingRect(contour)
        cv2.rectangle(img, (X, Y), (X + W, Y + H), (0,0,255), 2)
cv2.imshow('contour', img)

但上面的代码有这个输出： 的结果

如何找到不像“我”或阿拉伯字母那样不连续的字母的轮廓？

Answer 1

在找到轮廓之前，您可以使用一些分割方法：

rect_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (30, 10))
threshed = cv2.morphologyEx(img_thresh, cv2.MORPH_CLOSE, rect_kernel)

在应用cv2.findContours后，结果如下：

Answer 2

我有这个问题。我将其固定为这种方式。 添加此代码：

dst = cv2.Canny(gray, 0, 150)

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)    
  dst = cv2.Canny(gray, 0, 150)
blured = cv2.blur(dst, (5,5), 0)    
img_thresh = cv2.adaptiveThreshold(blured, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV, 11, 2)
imgContours, Contours, Hierarchy = cv2.findContours(img_thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
for contour in Contours:
    if cv2.contourArea(contour) > MIN_CONTOUR_AREA:
        [X, Y, W, H] = cv2.boundingRect(contour)
        cv2.rectangle(img, (X, Y), (X + W, Y + H), (0,0,255), 2)
cv2.imshow('contour', img)