上周做車牌號數字識別，網上找了字符分割的代碼（可以用，是老代碼），自己寫了單獨數字（0~9）的識別代碼（新代碼），新老代碼可以轉換，但是這兩段代碼不清楚怎么才可以合到一起？（下面是我自己和在一起的代碼，編譯沒問題，演算法有問題。）目前的的問題就是車牌號雖然分割了，但是分割的幾個字符怎么分別到單個數字識別的那個代碼里，一一識別出來，并且最后輸出車牌號數字。謝謝各位幫忙啦~~本周五及之前都可以的。。。給點提示或者幫我改下下。下面是代碼：
#include <opencv2/opencv.hpp>
#include <string.h>
#include <fstream>
#include <stdio.h>
#include <math.h>
#include <cv.h>
#include <highgui.h>
#include <cxcore.h>
#include <cvaux.h>
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
using namespace std;
using namespace cv;
void findX(IplImage* img, int* min, int* max)
{
int found = 0;
CvScalar maxVal = cvRealScalar(img->width * 255);
CvScalar val = cvRealScalar(0);
CvMat data;
int minCount = img->width * 255 / 5;
int count = 0;
for (int i = 0; i < img->width; i++) {
cvGetCol(img, &data, i);
val = cvSum(&data);
if (val.val[0] < maxVal.val[0]) {
count = val.val[0];
if (count > minCount && count < img->width * 255) {
*max = i;
if (found == 0) {
*min = i;
found = 1;
}
}
}
}
}
//找出含車牌文字的最上端，排除兩顆螺絲的位置
void findY(IplImage* img, int* min, int* max)
{
int found = 0;
CvScalar maxVal = cvRealScalar(img->height * 255);
CvScalar val = cvRealScalar(0);
CvMat data;
int minCount = img->width * 255 / 5;
int count = 0;
for (int i = 0; i < img->height; i++) {
cvGetRow(img, &data, i);
val = cvSum(&data);
if (val.val[0] < maxVal.val[0]) {
count = val.val[0];
if (count > minCount && count < img->height * 255) {
*max = i;
if (found == 0) {
*min = i;
found = 1;
}
}
}
}
}
//車牌字符的最小區域
CvRect findArea(IplImage* img)
{
int minX, maxX;
int minY, maxY;
findX(img, &minX, &maxX);
findY(img, &minY, &maxY);
CvRect rc = cvRect(minX, minY, maxX - minX, maxY - minY);
return rc;
}
Mat img_divide(Mat src)
{
Mat dst_gray,dst_gra,dst_gr;
int i=5;//矩陣大小
Mat dst( cvRound (src.rows/1), cvRound(src.cols/1), CV_8UC1 );
cvtColor( src, dst_gray, CV_BGR2GRAY );
resize( dst_gray, dst, dst.size(), 0, 0, INTER_LINEAR );
medianBlur (dst , dst_gra, i );
threshold( dst_gra, dst_gr, 0, 255,CV_THRESH_BINARY|CV_THRESH_OTSU );
//尋找最小區域,并截取
IplImage* pI = &dst_gr.operator IplImage();
CvRect rc = findArea(pI);
cvSetImageROI(pI, rc);
IplImage* img_gray2 = cvCreateImage(cvSize(rc.width, rc.height), IPL_DEPTH_8U, 1);
cvCopyImage(pI, img_gray2);
cvResetImageROI(pI);
IplImage* imgSrc2 = cvCreateImage(cvSize(rc.width, rc.height), IPL_DEPTH_8U, 3);
IplImage* P_src = &src.operator IplImage();
cvSetImageROI(P_src, rc);
cvCopyImage(P_src, imgSrc2);
cvResetImageROI(P_src);
//形態學
cvMorphologyEx(img_gray2, img_gray2, NULL, NULL, CV_MOP_CLOSE);
CvSeq* contours = NULL;
CvMemStorage* storage = cvCreateMemStorage(0);
int count = cvFindContours(img_gray2, storage, &contours,
sizeof(CvContour), CV_RETR_EXTERNAL);
int idx = 0;
char szName[56] = {0};
for (CvSeq* c = contours; c != NULL; c = c->h_next)
{
//cvDrawContours(imgSrc2, c, CV_RGB(255, 0, 0), CV_RGB(255, 255, 0), 100);
CvRect rc = cvBoundingRect(c);
cvDrawRect(imgSrc2, cvPoint(rc.x, rc.y), cvPoint(rc.x + rc.width, rc.y + rc.height), CV_RGB(255, 0, 0));
if (rc.width < imgSrc2->width / 10 && rc.height < imgSrc2->height / 5) { continue; }
}
IplImage* imgNo = cvCreateImage(cvSize(rc.width, rc.height), IPL_DEPTH_8U, 3);
cvSetImageROI(imgSrc2, rc);
cvCopyImage(imgSrc2, imgNo);
cvShowImage("src", imgNo);
Mat pic(imgNo);
cvWaitKey(0);
cvDestroyAllWindows();
return pic;
}
int img_gramme(Mat img,int* result)
{
vector<vector<Point> > contours;
vector<Vec4i> hierarchy;
float b[3],s[3],num[3];
int i;
/*int result[5];CV_THRESH_TOZERO|*/
CvPoint rect_pts[4], *pt = rect_pts;
Mat src_image;
threshold( img, src_image, 0, 255,CV_THRESH_BINARY );
img=src_image.clone();
findContours( src_image, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) ); //Find contours
vector<vector<Point> > contours_poly( contours.size() );
vector<Rect> boundRect( contours.size() );
for (i=0; i<contours.size(); i++)
{
s[i]=contourArea(contours[i]);
approxPolyDP( Mat(contours[i]), contours_poly[i], 3, true );
boundRect[i] = boundingRect( Mat(contours_poly[i]) );
result[0]=boundRect[i].x;
result[1]=boundRect[i].y;
result[2]=boundRect[i].width;
result[3]=boundRect[i].height;
s[i]=s[i]/(result[2]*result[3]);
b[i]=(float)result[2]/result[3];
boundRect[i].height=boundRect[i].height/2;
IplImage* pI = &img.operator IplImage();
cvSetImageROI(pI, boundRect[i]);
Mat img_half(pI);
num[i]=countNonZero(img_half);
num[i]=num[i]/(result[2]*result[3]);
cout<<"-面積："<<s[i]<<" ";
cout<<"-長寬比："<<b[i]<<" ";
cout<<"-長："<<result[2]<<" ";
cout<<"-寬："<<result[3]<<" ";
cout<<"半邊面積"<<num[i]<<endl;
}
if(contours.size()==3) return 8;
else if(contours.size()==2)
{
if(b[1]<0.44&&b[0]>0.48&&b[0]<0.49) return 0;
else if(b[1]>0.49&&b[1]<0.6&&b[0]>0.49&&b[0]<0.508) return 4;
else if(b[1]>0.7&&b[1]<0.8&&b[0]>0.47&&b[0]<=0.48) return 9;
else if(b[1]>0.83&&b[1]<=1&&b[0]>0.508&&b[0]<0.6&&num[0]>0.14&&num[0]<0.19) return 6;
}
else if(contours.size()==1)
{
if(num[0]>0.15&&num[0]<0.2) return 2;
else if(num[0]>0.27&&num[0]<0.3) return 5;
else if(num[0]>0.48&&num[0]<0.6) return 1;
else if(num[0]>0.21&&num[0]<26)
if(s[0]>0.26&&s[0]<0.3) return 7;
else if(s[0]>0.35&&s[0]<0.45) return 3;
}
else return 11;
}
int main()
{
Mat src, dst_gr, src_image;
int result[5],data;
string pstrImageName;
string cmd;
string pstrWindowsDstTitle = "縮放圖";
cout<<"What do you want to test ?"<<endl;
while(true)
{
waitKey(10);
cin>>pstrImageName;
src = imread( pstrImageName);
dst_gr=img_divide(src);
data=https://bbs.csdn.net/topics/img_gramme(dst_gr,result);
cout<<"the num is : "<<data<<" !"<<endl;
imshow(pstrWindowsDstTitle,dst_gr);
}
waitKey(0);
return 0;
}
uj5u.com熱心網友回復：
樓主你好，請問你的問題解決了嗎？我最近也在做這個，遇到類似問題，求助樓主！uj5u.com熱心網友回復：
車牌識別做出來了嗎？轉載請註明出處，本文鏈接：https://www.uj5u.com/houduan/81040.html
標籤：數據庫及相關技術