从图像中删除行

Question

我是OpenCV的初学者，我需要删除图像中的水平和垂直线条，以便只保留文本（这些行在提取ocr文本时会造成麻烦）。我正在尝试从营养成分表中提取文本。谁能帮我？

Answer 1

这是一个有趣的问题，所以我给它一个镜头。下面我会告诉你如何提取和删除水平和垂直线。你可以从中推断出来。另外，为了节省时间，我没有预处理图像，以便像应该那样突出背景，这是一个改进的途径。

其结果是： 代码（编辑：附加的垂直线）：

#include <iostream> 
#include <opencv2/opencv.hpp> 
using namespace std; 
using namespace cv; 
int main(int, char** argv) 
{ 
    // Load the image 
    Mat src = imread(argv[1]); 
    // Check if image is loaded fine 
    if(!src.data) 
     cerr << "Problem loading image!!!" << endl; 
    Mat gray; 
    if (src.channels() == 3) 
    { 
     cvtColor(src, gray, CV_BGR2GRAY); 
    } 
    else 
    { 
     gray = src; 
    } 

    //inverse binary img 
    Mat bw; 
    //this will hold the result, image to be passed to OCR 
    Mat fin; 
    //I find OTSU binarization best for text. 
    //Would perform better if background had been cropped out 
    threshold(gray, bw, 0, 255, THRESH_BINARY_INV | THRESH_OTSU); 
    threshold(gray, fin, 0, 255, THRESH_BINARY | THRESH_OTSU); 
    imshow("binary", bw); 
    Mat dst; 
    Canny(fin, dst, 50, 200, 3); 
    Mat str = getStructuringElement(MORPH_RECT, Size(3,3)); 
    dilate(dst, dst, str, Point(-1, -1), 3); 
    imshow("dilated_canny", dst); 
    //bitwise_and w/ canny image helps w/ background noise 
    bitwise_and(bw, dst, dst); 
    imshow("and", dst); 
    Mat horizontal = dst.clone(); 
    Mat vertical = dst.clone(); 
    fin = ~dst; 

    //Image that will be horizontal lines 
    Mat horizontal = bw.clone(); 
    //Selected this value arbitrarily 
    int horizontalsize = horizontal.cols/30; 
    Mat horizontalStructure = getStructuringElement(MORPH_RECT, Size(horizontalsize,1)); 
    erode(horizontal, horizontal, horizontalStructure, Point(-1, -1)); 
    dilate(horizontal, horizontal, horizontalStructure, Point(-1, -1), 1); 
    imshow("horizontal_lines", horizontal); 

    //Need to find horizontal contours, so as to not damage letters 
    vector<Vec4i> hierarchy; 
    vector<vector<Point> >contours; 
    findContours(horizontal, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_NONE); 
    for (const auto& c : contours) 
    { 
     Rect r = boundingRect(c); 

     float percentage_height = (float)r.height/(float)src.rows; 
     float percentage_width = (float)r.width/(float)src.cols; 

     //These exclude contours that probably are not dividing lines 
     if (percentage_height > 0.05) 
      continue; 

     if (percentage_width < 0.50) 
      continue; 
     //fills in line with white rectange 
     rectangle(fin, r, Scalar(255,255,255), CV_FILLED); 
    } 

    int verticalsize = vertical.rows/30; 
    Mat verticalStructure = getStructuringElement(MORPH_RECT, Size(1,verticalsize)); 
    erode(vertical, vertical, verticalStructure, Point(-1, -1)); 
    dilate(vertical, vertical, verticalStructure, Point(-1, -1), 1); 
    imshow("verticalal", vertical); 

    findContours(vertical, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_NONE); 
    for (const auto& c : contours) 
    { 
     Rect r = boundingRect(c); 

     float percentage_height = (float)r.height/(float)src.rows; 
     float percentage_width = (float)r.width/(float)src.cols; 

     //These exclude contours that probably are not dividing lines 
     if (percentage_width > 0.05) 
      continue; 

     if (percentage_height < 0.50) 
      continue; 
     //fills in line with white rectange 
     rectangle(fin, r, Scalar(255,255,255), CV_FILLED); 
    } 

    imshow("Result", fin); 
    waitKey(0); 
    return 0; 
} 

这种方法的局限性是，该线需要是直的。由于底线的曲线，它在“能量”中略微削减为“E”。也许像建议的那样（我从来没有使用过）检测到hough线，可以设计出类似但更稳健的方法。另外，用矩形填充线条可能不是最好的方法。