Python OpenCV去除字母后面的杂线操作

原图

代码

 src = cv2.imread("28.png")
 gray_src = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
 #cv2.imshow("input image", src)
 #cv2.imshow("gray image", gray_src)
 #cv2.waitKey(0)
 gray_src = cv2.bitwise_not(gray_src)
 #二值化
 binary_src = cv2.adaptiveThreshold(gray_src, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 15, -2)
 cv2.namedWindow("result image", cv2.WINDOW_AUTOSIZE)
 cv2.imshow("result image", binary_src)
 #cv2.waitKey(0)
 # 提取水平线  src.shape[1]得到src列数
 #hline = cv2.getStructuringElement(cv2.MORPH_RECT, (1, 1), (-1, -1))
 hline = cv2.getStructuringElement(cv2.MORPH_RECT, (1, 4), (-1, -1)) #定义结构元素，卷积核
 # 提取垂直线  src.shape[0]得到src行数
 vline = cv2.getStructuringElement(cv2.MORPH_RECT, (4, 1), (-1, -1))
 #vline = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3))
 # 这两步就是形态学的开操作——先腐蚀再膨胀
 #temp = cv2.erode(binary_src, hline)   #腐蚀
 #dst = cv2.dilate(temp, hline)      #膨胀
 # 开运算
 dst = cv2.morphologyEx(binary_src, cv2.MORPH_OPEN, hline)  #水平方向
 dst = cv2.morphologyEx(dst, cv2.MORPH_OPEN, vline)  #垂直方向
 #将二指图片的效果反转既黑色变白色，白色变黑色。 非操作
 dst = cv2.bitwise_not(dst)
 cv2.imshow("Final image", dst)
 cv2.waitKey(0)

结果图，还有一些点需要进一步处理

补充知识：Opencv 提取水平 垂直线，去除杂线，提取对象

我就废话不多说了，大家还是直接看代码吧~

#include<opencv2\opencv.hpp>
#include<iostream>

using namespace std;
using namespace cv;

int main(int argc, char* argv[])
{
Mat src = imread("截图3.jpg");
if (src.empty())
{
return -1;
}
String strInput = "input image";
namedWindow(strInput, CV_WINDOW_AUTOSIZE);
imshow(strInput, src);
Mat dst;
cvtColor(src, dst, CV_BGR2GRAY);//转灰度
imshow("output grap image", dst);
Mat binimg;
adaptiveThreshold(~dst, binimg, 255, ADAPTIVE_THRESH_MEAN_C, ADAPTIVE_THRESH_MEAN_C, 15, -2);//转二值
imshow("binary image", binimg);
Mat hLine = getStructuringElement(MORPH_RECT, Size(src.cols/16, 1), Point(-1, -1));//水平结构
Mat vLine = getStructuringElement(MORPH_RECT, Size(1, src.rows / 16), Point(-1, -1));//垂直结构

Mat kernel = getStructuringElement(MORPH_RECT, Size(3, 3), Point(-1, -1));//去除杂线 提取对象
Mat tmp;
//erode(binimg, tmp, vLine);
//dilate(tmp, dst, vLine);
morphologyEx(binimg, dst, CV_MOP_OPEN,hLine);
bitwise_not(dst, dst);//取反
blur(dst, dst, Size(3, 3), Point(-1, -1));
imshow("Final image", dst);

waitKey(0);
return 0;
}

来源：https://blog.csdn.net/sxlsxl119/article/details/80223729