字母似乎总是在数字的末尾。如果这是真的，您可以采用更简单的方法：找到所有轮廓

创建边界框列表(即每个轮廓对应一个框)

确定哪一个是最右边的边界框

使用所有其他框的(x，y，width，height)信息来创建一个ROI并只裁剪数字

Python 2.7和opencv2.4的源代码：import cv2

### load input image and convert it to grayscale

img = cv2.imread("input.png")

print("img shape=", img.shape)

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

#### extract all contours

_, contours, _ = cv2.findContours(gray.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

# debug: draw all contours

#cv2.drawContours(img, contours, -1, (0, 0, 255), 2)

#cv2.imwrite("all_contours.jpg", img)

#### create one bounding box for every contour found

bb_list = []

for c in contours:

bb = cv2.boundingRect(c)

# save all boxes except the one that has the exact dimensions of the image (x, y, width, height)

if (bb[0] == 0 and bb[1] == 0 and bb[2] == img.shape[1] and bb[3] == img.shape[0]):

continue

bb_list.append(bb)

# debug: draw boxes

#img_boxes = img.copy()

#for bb in bb_list:

# x,y,w,h = bb

# cv2.rectangle(img_boxes, (x, y), (x+w, y+h), (0, 0, 255), 2)

#cv2.imwrite("boxes.jpg", img_boxes)

#### sort bounding boxes by the X value: first item is the left-most box

bb_list.sort(key=lambda x:x[0])

# debug: draw the last box of the list (letter M)

#print("letter M @ ", bb_list[-1])

#x,y,w,h = bb_list[-1]

#cv2.rectangle(img, (x, y), (x+w, y+h), (0, 0, 255), 2)

#cv2.imwrite("last_contour.jpg", img)

### remove the last item from the list, i.e. remove box for letter M

bb_list = bb_list[:-1]

### and now the fun part: create one large bounding box to rule them all

x_start, _, _, _ = bb_list[0]

x_end, _, w_end, _ = bb_list[-1]

x = x_start

w = (x_end + w_end) - x_start

bb_list.sort(key=lambda y:y[1]) # sort by Y value: the first item has the smallest Y value

_, y, _, _ = bb_list[0]

bb_list.sort(key=lambda y:y[3]) # sort by Height value: the last item has the largest Height value

_, _, _, h = bb_list[-1]

print("x=", x, "y=", y, "w=", w, "h=", h)

# debug: draw the final region of interest

roi_img = img.copy()

cv2.rectangle(roi_img, (x, y), (x+w, y+h), (0, 0, 255), 2)

cv2.imwrite("roi.jpg", roi_img)

# crop to the roi

crop_img = img[y:y+h, x:x+w]

cv2.imwrite("crop.jpg", crop_img)