最近尝试使用opencv拼接图像时，在提取完特征点，匹配对应点，坐标转换至同一坐标，平滑图像后，图片存在黑色的边缘。搜索一番没能找到现成的轮子。想起之前LeetCode打卡的85. 最大矩形 参考其中算法，简单修改后得到如下代码。
from datetime import datetime
import cv2
import numpy as np
def maximalRectangle(matrix, mask=255):
"""二值矩阵获取最大矩形"""
n, m = matrix.shape
left = np.zeros([n, m])
for i in range(n):
for j in range(m):
if matrix[i, j] == mask:
if j == 0:
left[i, j] = 1
else:
left[i, j] = left[i, j - 1] + 1
ret = 0
ans_x = 0
ans_y = 0
ans_w = 0
ans_h = 0
for i in range(m):
tmp_ret, y, w, h = largestRectangleArea(left[:, i])
if tmp_ret > ret:
ret = tmp_ret
ans_x = i - w + 1
ans_y = y
ans_w = w
ans_h = h
return ans_x, ans_y, ans_w, ans_h
def largestRectangleArea(heights):
"""直方图获取最大矩形"""
n = len(heights)
left, right = [0] * n, [n] * n
mono_stack = list()
for i in range(n):
while mono_stack and heights[mono_stack[-1]] >= heights[i]:
right[mono_stack[-1]] = i
mono_stack.pop()
left[i] = mono_stack[-1] if mono_stack else -1
mono_stack.append(i)
ans = 0
y = 0
w = 0
h = 0
for i in range(n):
tmp = (right[i] - left[i] - 1) * heights[i]
if tmp > ans:
ans = tmp
y = left[i] + 1
w = int(heights[i])
h = right[i] - left[i] - 1
return ans, y, w, h
def get_binary_pic(img, threshold=0, mask=255):
"""获取二值图像"""
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
_, thresh = cv2.threshold(gray, threshold, mask, cv2.THRESH_BINARY)
return thresh
def cut_picture(img, threshold=0):
"""返回最大有效内接矩形的图片"""
print("cut_picture start...", datetime.now())
ans_x, ans_y, ans_w, ans_h = maximalRectangle(get_binary_pic(img,threshold))
print("cut_picture end...", datetime.now())
return img[ans_y:ans_y + ans_h, ans_x:ans_x + ans_w, :]
使用方法：
直接调用cut_picture函数即可，输入为需要裁剪cv2读取到的图像，输出为该图像裁剪为最大内接矩形后的图像。
可选参数threshold为生成二值图像的阈值
