使用openCV去除文字中乱入的线条实例

void findLines(IplImage* raw, IplImage* dst)
{
	IplImage* src = cvCloneImage(raw);
	IplImage* canny = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1);
	cvCanny(src, canny, 20, 200, 3);
	CvMemStorage* stor = cvCreateMemStorage(0);
	CvSeq* lines = NULL;
	lines = cvHoughLines2(canny, stor, CV_HOUGH_PROBABILISTIC, 1, CV_PI / 180, 80, 200, 30);
	cvZero(dst);
	CvPoint maxStart, maxEnd;
	int maxDistance = 0;
	for (int i = 0; i < lines->total; i++)
	{
		CvPoint* line = (CvPoint*)cvGetSeqElem(lines, i);
		if (abs(line[0].x - line[1].x) > maxDistance)
		{
			maxDistance = abs(line[0].x - line[1].x);
			maxStart = line[0];
			maxEnd = line[1];
		}
	}
	cvLine(dst, maxStart, maxEnd, cvScalar(255), 1);
	cvReleaseImage(&src);
	cvReleaseMemStorage(&stor);
}

void eraseLine(IplImage* src, IplImage* flag)
{// flag为图1.2所示的图片，src为图1.1所示的二值化图片
	for (int row = 0; row < src->height; row++)
		for (int col = 0; col < src->width; col++)
		{	// 如果在白色线段上，则将二值化图片填为白色
			if (cvGet2D(flag, row, col).val[0] == 255)
				cvSet2D(src, row, col, cvScalar(255));
		}
}

#include <cv.h>
#include <highgui.h>
#include <iostream>
using namespace std;
/*
函数功能：在输入图像中找一条直线
输入输出：输入的图像是灰度图raw，返回值为dst，返回值是一条白色的线
lines = cvHoughLines2(canny, stor, CV_HOUGH_PROBABILISTIC, 1, CV_PI / 180, 80, 200, 30);
参数中的200是指要找的直线长度要在200个像素以上；
参数中的30指的是两条在同一直线上的线段，如果相隔不到30，则把它们连起来
*/
void findLines(IplImage* raw, IplImage* dst)
{
 IplImage* src = cvCloneImage(raw); // clone the input image
 IplImage* canny = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1); // create a tmp image head to save gradient image
 cvCanny(src, canny, 20, 200, 3); // Generate its gradient image
 CvMemStorage* stor = cvCreateMemStorage(0);
 CvSeq* lines = NULL;
 // find a line whose length bigger than 200 pixels
 lines = cvHoughLines2(canny, stor, CV_HOUGH_PROBABILISTIC, 1, CV_PI / 180, 80, 200, 30);
 cvZero(dst);
 CvPoint maxStart, maxEnd; // save the coordinate of the head and rear of the line we want
 int maxDistance = 0; // The maximum distance of all lines found by [cvHoughLines2]
 for (int i = 0; i < lines->total; i++) // lines->total: the number of lines 
 {
 // variable 'lines' is a sequence, [cvGetSeqElem] gets the (i)th line, and it returns its head and rear.
 CvPoint* line = (CvPoint*)cvGetSeqElem(lines, i); 
 // line[0] and line[1] is respectively the line's coordinate of its head and rear
 if (abs(line[0].x - line[1].x) > maxDistance)
 {/* It's a trick because the line is almost horizontal.
 strictly, it should be 
 sqrt((line[0].x - line[1].x)*(line[0].x - line[1].x)+(line[0].y - line[1].y)*(line[0].x - line[1].x))
 */
 maxDistance = abs(line[0].x - line[1].x);
 maxStart = line[0];
 maxEnd = line[1];
 }
 }
 cvLine(dst, maxStart, maxEnd, cvScalar(255), 1); // draw the white line[cvScalar(255)] in a black background
 cvReleaseImage(&src); // free the memory
 cvReleaseMemStorage(&stor);
}
/*
函数功能：擦除面积小于【15个像素】的小块儿
输入输出：无返回值，直接对输入的图像进行操作
*/
void erase(IplImage* raw)
{
 IplImage* src = cvCloneImage(raw);
 /*Binarization and inverse the black and white because the function next only find white area while
 the word in image is black.*/
 cvThreshold(src, src, 120, 255, CV_THRESH_BINARY_INV); 
 // create some space to save the white areas but we access it via variable 'cont'
 CvMemStorage* stor = cvCreateMemStorage(0); 
 CvSeq* cont;
 cvFindContours(src, stor, &cont, sizeof(CvContour), CV_RETR_EXTERNAL); // find the white regions
 for (; cont; cont = cont->h_next) // Traversal
 {
 if (fabs(cvContourArea(cont)) < 15) // if its Area smaller than 15, we fill it with white[cvScalar(255)]
 cvDrawContours(raw, cont, cvScalar(255), cvScalar(255), 0, CV_FILLED, 8);
 }
 cvReleaseImage(&src);
}
 
int main()
{
 IplImage* src = cvLoadImage("D:/test.png");
 cvNamedWindow("原图", 1);
 cvShowImage("原图", src);
 IplImage* gray = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1);
 IplImage* canny = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1);
 IplImage* dst = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1);
 IplImage* binary = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1);
 
 cvCvtColor(src, gray, CV_RGB2GRAY);
 cvThreshold(gray, binary, 120, 255, CV_THRESH_OTSU);
 
 findLines(gray, dst);
 cvNamedWindow("dst", 1);
 cvShowImage("dst", dst);
 
 for (int row = 0; row < binary->height; row++)
 for (int col = 0; col < binary->width; col++)
 {
 if (cvGet2D(dst, row, col).val[0] == 255)
 {
 int up = 0, down = 0;
 int white = 0;
 for (int i = row; i >= 0; i--)
 {
 if (cvGet2D(binary, i, col).val[0] == 0)
 {
 up++; 
 white = 0;
 }
 else white++;
 if(white > 2) break;
 }
 white = 0;
 for (int i = row; i < binary->height; i++)
 {
 if (cvGet2D(binary, i, col).val[0] == 0)
 {
 down++;
 white = 0;
 }
 else white++;
 if (white > 2) break;
 }
 if (up + down < 8)
 {
 for (int i = -up; i <= down; i++) cvSet2D(binary, row + i, col, cvScalar(255));
 }
 }
 }
 cvNamedWindow("结果", 1);
 cvShowImage("结果", binary);
 erase(binary);
 //cvDilate(binary, binary, NULL, 1);
 cvErode(binary, binary, NULL, 1);
 cvNamedWindow("膨胀腐蚀", 1);
 cvShowImage("膨胀腐蚀", binary);
 cvSaveImage("D:/result.png", binary);
 cvReleaseImage(&src);
 cvReleaseImage(&canny);
 cvReleaseImage(&gray);
 cvReleaseImage(&dst);
 cvReleaseImage(&binary);
 cvWaitKey(0);
 return 0;
}