c++ - Removing lines from image -

i beginner in opencv, need remove horizontal , vertical lines in image text remains ( lines causing trouble when extracting text in ocr ). trying extract text nutrient fact table. can me?

this interesting question, gave shot. below show how extract , remove horizontal , vertical lines. extrapolate it. also, sake of saving time, did not preprocess image crop out background 1 should, avenue improvement.

the result: code (edit: added vertical lines):

#include <iostream> #include <opencv2/opencv.hpp> using namespace std; using namespace cv; int main(int, char** argv) {     // load image     mat src = imread(argv[1]);     // check if image 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 hold result, image passed ocr     mat fin;     //i find otsu binarization best 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 horizontal lines     mat horizontal = bw.clone();     //selected 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 find horizontal contours, not damage letters     vector<vec4i> hierarchy;     vector<vector<point> >contours;     findcontours(horizontal, contours, hierarchy, cv_retr_tree, cv_chain_approx_none);     (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 not dividing lines         if (percentage_height > 0.05)             continue;          if (percentage_width < 0.50)             continue;         //fills in line 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);     (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 not dividing lines         if (percentage_width > 0.05)             continue;          if (percentage_height < 0.50)             continue;         //fills in line white rectange         rectangle(fin, r, scalar(255,255,255), cv_filled);     }      imshow("result", fin);     waitkey(0);     return 0; } 

the limitations of approach lines need straight. due curve in bottom line, cuts "e" in "energy". perhaps hough line detection suggested (i've never used it), similar more robust approach devised. also, filling in lines rectangles not best approach.