<em>Mac</em>Book项目 2009年学校开始实施<em>Mac</em>Book项目,所有师生配备一本<em>Mac</em>Book,并同步更新了校园无线网络。学校每周进行电脑技术更新,每月发送技术支持资料,极大改变了教学及学习方式。因此2011
2021-06-01 09:32:01
OpenCV3實現車牌識別(C++版)
2022-08-01 14:03:25
本文範例為大家分享了OpenCV3實現車牌識別的具體程式碼，供大家參考，具體內容如下
車牌識別（基於OpenCV3.4.7+VS2017）
視訊識別
藍色車牌識別
視覺入坑的第一個Demo（註釋很詳細），因為本人之前拖延，一直沒能寫詳細實現部落格，先將程式碼貼出來供大家交流，個人認為精華部分在字元切割（直接用指標遍歷畫素加限制條件切割），車牌模板已上傳，整個工程也已上傳，後續完善各環節實現步驟詳解。
標頭檔案：Global.h
#ifdef GLOBAL
extern int flag_1;
extern bool flag;
extern bool specialFlag;
extern int captureRead
extern string carPlate;
extern char test[10];
extern struct stu1
{
char number;
Mat image;
double matchDegree;
};
extern struct stu
{
Mat image;
double matchDegree;
};
#endif唯一的.cpp檔案：PlateIdentify.cpp（說實話，這Demo挺 “C” 的）
#include <opencv2/opencv.hpp>
#include<opencv2/imgproc/imgproc.hpp>
#include<opencv2/highgui/highgui.hpp>
#include"Global.h"
#include <windows.h>
#include <string>
using namespace std;
using namespace cv;
void fillHole(const Mat srcBw, Mat &dstBw); //填補演演算法
Mat cutOne(Mat cutImage); //邊框切割演演算法
void CharCut(Mat srcImage); //單個字元切割演演算法
Mat Location(Mat srcImage); //影象識別演演算法
void SingleCharCut(Mat doubleImage, int k1, int k2);
void ShowChar();
void MatchProvince();
void MatchNumber();
void readProvince();
void readNumber();
void VideoShow(Mat videoImage);
void GetStringSize(HDC hDC, const char* str, int* w, int* h);
void putTextZH(Mat &dst, const char* str, Point org, Scalar color, int fontSize, const char* fn, bool italic, bool underline);
int flag_1; //判斷是否傾斜，需不需要二次定位車牌
bool flag; //判斷提取是否成功
bool specialFlag = false; //針對巢狀車牌
int captureRead = 0;
int videoFlag = 0;
string carPlateProvince = " ";
string carPlate = " ";
char test[10];
vector<Mat> singleChar; //字元圖片容器
int main(int argc, char *argv[])
{
//計時開始
double time0 = static_cast<double>(getTickCount());
//視訊操作
VideoCapture capture("1.mp4");
Mat srcImage;
Mat theFirst;
int singleCharLength;
//讀取字元圖片
readProvince();
readNumber();
while (1) {
capture >> srcImage;
try {
if (!srcImage.data) { printf("視訊識別結束 n"); return 0; }
if (srcImage.rows >= srcImage.cols)
{
resize(srcImage, srcImage, Size(640, 640 * srcImage.rows / srcImage.cols));
}
else
{
resize(srcImage, srcImage, Size(400 * srcImage.cols / srcImage.rows, 400));
}
//車牌定位
theFirst = Location(srcImage);
if (flag)
{
if (flag_1 == 1) //旋轉後要再次定位去上下雜邊
{
theFirst = Location(theFirst);
flag_1 = 0;
}
}
if (flag)
{
//車牌切割(切割上下邊，去除干擾)
theFirst = cutOne(theFirst);
//單個字元切割
CharCut(theFirst);
singleCharLength = singleChar.size();
printf("採取字元輪廓數 %dn", singleCharLength);
ShowChar();
if (singleCharLength >= 7)
{
MatchProvince();
MatchNumber();
}
singleChar.clear();
}
}
catch (Exception e) {
cout << "Standard ecxeption : " << e.what() << " n" << endl;
}
if (waitKey(30) >= 0)
break;
//延時30ms
}
//imwrite("match\xxxxxx.bmp", singleChar[2]);
time0 = ((double)getTickCount() - time0) / getTickFrequency();
cout << "執行時間" << time0 << "秒" << endl;
waitKey(0);
}
void fillHole(const Mat srcBw, Mat &dstBw)
{
Size imageSize = srcBw.size();
Mat Temp = Mat::zeros(imageSize.height + 2, imageSize.width + 2, srcBw.type());//延展影象
srcBw.copyTo(Temp(Range(1, imageSize.height + 1), Range(1, imageSize.width + 1)));
cv::floodFill(Temp, Point(0, 0), Scalar(255));
Mat cutImg;//裁剪延展的影象
Temp(Range(1, imageSize.height + 1), Range(1, imageSize.width + 1)).copyTo(cutImg);
dstBw = srcBw | (~cutImg);
}
Mat Location(Mat srcImage)
{
//判斷變數重賦值
flag = false;
//用於旋轉車牌
int imageWidth, imageHeight; //輸入影象的長和寬
imageWidth = srcImage.rows; //獲取圖片的寬
imageHeight = srcImage.cols; //獲取影象的長
//!!!!!!!!!!!!!!!!!!!
Mat blueROI = srcImage.clone();
cvtColor(blueROI, blueROI, CV_BGR2HSV);
//namedWindow("hsv圖");
//imshow("hsv圖", blueROI);
//中值濾波操作
medianBlur(blueROI, blueROI, 3);
//namedWindow("medianBlur圖");
//imshow("medianBlur圖", blueROI);
//將藍色區域二值化
inRange(blueROI, Scalar(100, 130, 50), Scalar(124, 255, 255), blueROI);
//namedWindow("blue圖");
//imshow("blue圖", blueROI);
Mat element1 = getStructuringElement(MORPH_RECT, Size(2, 2)); //size（）對速度有影響
morphologyEx(blueROI, blueROI, MORPH_OPEN, element1);
//namedWindow("0次K運算後影象");
//imshow("0次K運算後影象", blueROI);
Mat element0 = getStructuringElement(MORPH_ELLIPSE, Size(10, 10)); //size（）對速度有影響
morphologyEx(blueROI, blueROI, MORPH_CLOSE, element0);
//namedWindow("0次閉運算後影象");
//imshow("0次閉運算後影象", blueROI);
vector<vector<Point>> contours;
findContours(blueROI, contours, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE);
int cnt = contours.size();
cout << "number of contours " << cnt << endl; //列印輪廓個數
if (cnt == 0)
{
if (!flag) //在視訊中顯示
{
cout << "圖中無車牌 " << endl;
//namedWindow("提取車牌結果圖");
//imshow("提取車牌結果圖", srcImage); //顯示最終結果圖
VideoShow(srcImage);
return srcImage;
}
}
double area;
double longside, temp, shortside, long2short;
float angle = 0;
Rect rect;
RotatedRect box; //可旋轉的矩形盒子
Point2f vertex[4]; //四個頂點
Mat image = srcImage.clone(); //為後來顯示做準備
Mat rgbCutImg; //車牌裁剪圖
//box.points(vertex); //獲取矩形四個頂點座標
//length=arcLength(contour[i]); //獲取輪廓周長
//area=contourArea(contour[i]); //獲取輪廓面積
//angle=box.angle; //得到車牌傾斜角度
for (int i = 0; i < cnt; i++)
{
area = contourArea(contours[i]); //獲取輪廓面積
if (area > 600 && area < 15000) //矩形區域面積大小判斷
{
rect = boundingRect(contours[i]); //計算矩形邊界
box = minAreaRect(contours[i]); //獲取輪廓的矩形
box.points(vertex); //獲取矩形四個頂點座標
angle = box.angle; //得到車牌傾斜角度
longside = sqrt(pow(vertex[1].x - vertex[0].x, 2) + pow(vertex[1].y - vertex[0].y, 2));
shortside = sqrt(pow(vertex[2].x - vertex[1].x, 2) + pow(vertex[2].y - vertex[1].y, 2));
if (shortside > longside) //短軸大於長軸，交換資料
{
temp = longside;
longside = shortside;
shortside = temp;
cout << "交換" << endl;
}
else
angle += 90;
long2short = longside / shortside;
if (long2short > 1.5 && long2short < 4.5)
{
flag = true;
for (int i = 0; i < 4; ++i) //劃線框出車牌區域
line(image, vertex[i], vertex[((i + 1) % 4) ? (i + 1) : 0], Scalar(0, 255, 0), 1, CV_AA);
if (!flag_1) //在視訊中顯示
{
printf("提取成功n");
/*namedWindow("提取車牌結果圖");
imshow("提取車牌結果圖", image); */ //顯示最終結果圖
VideoShow(image);
}
rgbCutImg = srcImage(rect);
//namedWindow("車牌圖");
//imshow("車牌圖", rgbCutImg);//裁剪出車牌
break; //退出迴圈，以免容器中變數變換
}
}
}
cout << "傾斜角度：" << angle << endl;
if (flag && fabs(angle) > 0.8) //車牌過偏，轉一下 偏移角度小時可不呼叫，後續找到合適範圍再改進
{
flag_1 = 1;
Mat RotractImg(imageWidth, imageHeight, CV_8UC1, Scalar(0, 0, 0)); //傾斜矯正圖片
Point2f center = box.center; //獲取車牌中心座標
Mat M2 = getRotationMatrix2D(center, angle, 1); //計算旋轉加縮放的變換矩陣
warpAffine(srcImage, RotractImg, M2, srcImage.size(), 1, 0, Scalar(0)); //進行傾斜矯正
//namedWindow("傾斜矯正後圖片",0);
//imshow("傾斜矯正後圖片", RotractImg);
rgbCutImg = RotractImg(rect); //擷取車牌彩色照片
//namedWindow("矯正後車牌照");
//imshow("矯正後車牌照", rgbCutImg);
/*cout << "矩形中心:" << box.center.x << "," << box.center.y << endl;*/
return rgbCutImg;
}
if (flag == false) {
printf("提取失敗n"); //後期加邊緣檢測法識別
if (!flag_1) //在視訊中顯示
{
/*namedWindow("提取車牌結果圖");
imshow("提取車牌結果圖", image); */ //顯示最終結果圖
VideoShow(image);
}
}
return rgbCutImg;
}
Mat cutOne(Mat cutImage)
{
//列印車牌長寬
try {
/*cout << " cutImage.rows : " << cutImage.rows << endl;
cout << " cutImage.cols : " << cutImage.cols << endl;*/
if(cutImage.rows >= cutImage.cols)
resize(cutImage, cutImage, Size(320, 320 * cutImage.rows / cutImage.cols));
}
catch (Exception e)
{
resize(cutImage, cutImage, Size(320, 100));
}
/*namedWindow("Resize車牌圖");
imshow("Resize車牌圖", cutImage);*/
int height = cutImage.rows;
cout << "tHeight:" << height << "tWidth:" << 320 << endl;
if (height < 86)
{
//!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!處理新型巢狀車牌!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
printf("巢狀車牌n");
specialFlag = true;
}
Mat whiteROI = cutImage.clone();
if (specialFlag)
{
cvtColor(whiteROI, whiteROI, CV_BGR2HSV);
//將白色區域二值化
//inRange(whiteROI, Scalar(0, 0, 0), Scalar(130, 50, 245), whiteROI); //增大 S 即飽和度可以使hsv白色檢測範圍更大
inRange(whiteROI, Scalar(0, 0, 0), Scalar(180, 100, 245), whiteROI);
//namedWindow("specialFlagwhiteROI圖");
//imshow("specialFlagwhiteROI圖", whiteROI);
}
else
{
GaussianBlur(whiteROI, whiteROI, Size(3, 3), 0, 0);
/*namedWindow("GaussianBlur車牌圖");
imshow("GaussianBlur車牌圖", whiteROI);*/
cvtColor(whiteROI, whiteROI, CV_BGR2HSV);
//medianBlur(whiteROI, whiteROI, 3);
//namedWindow("Src_medianBlur圖");
//imshow("Src_medianBlur圖", whiteROI);
//將白色區域二值化
//inRange(whiteROI, Scalar(0, 0, 10), Scalar(180, 30, 255), whiteROI); //增大 S 即飽和度可以使hsv白色檢測範圍更大
inRange(whiteROI, Scalar(0, 0, 10), Scalar(180, 120, 255), whiteROI);
//namedWindow("whiteROI圖");
//imshow("whiteROI圖", whiteROI);
}
/*
Mat element0 = getStructuringElement(MORPH_ELLIPSE, Size(4, 4)); //size（）對速度有影響
morphologyEx(whiteROI, whiteROI, MORPH_OPEN, element0);
namedWindow("OPEN圖");
imshow("OPEN圖", whiteROI);
*/
Mat dstImage = cutImage.clone();
vector<vector<Point>> contours;
findContours(whiteROI, contours, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE);
drawContours(dstImage, contours, -1, Scalar(0, 0, 255), 1);
//namedWindow("疑似字元輪廓識別圖");
//imshow("疑似字元輪廓識別圖", dstImage);
inRange(dstImage, Scalar(0, 0, 255), Scalar(0, 0, 255), dstImage);
//namedWindow("字元大輪廓圖");
//imshow("字元大輪廓圖", dstImage);
/*fillHole(dstImage, dstImage);
namedWindow("填補輪廓後圖");
imshow("填補輪廓後圖", dstImage);*/
int row1 = 2;
int row2 = dstImage.rows;
int rowMax = dstImage.rows - 1; //開區間，防止越界
int colMax = dstImage.cols - 1; //開區間，防止越界
int addFirst = 10;
int addFirst0 = 0;
int addFirst1 = 0;
int addFirst2 = 0;
//測中間畫素
//dstImage.at<uchar>(rowMax-1, colMax-1);
//cout << "Width:" << j << endl;
int addFirstTemp = addFirst; //第一次用時已經改變數值，容易忽略！！！！！
uchar* data;
//裁剪上下邊。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。
//上邊
for (int i = 2; i < rowMax / 3; i++, addFirst1 = 0) // 6 剛剛好
{
data = dstImage.ptr<uchar>(i);
for (int j = 2; j < colMax; j++)
{
if (data[j] == 255)
{
addFirst1++;
}
}
if (addFirst1 < addFirst) //篩選最小值所在行
{
row1 = i;
addFirst = addFirst1 + 3;
//cout << "行頭" << row1 << endl;
//flag_x = 1;
}
}
//下邊
for (int i = rowMax - 2; i > rowMax - rowMax / 4; i--, addFirst2 = 0) // 6 剛剛好
{
data = dstImage.ptr<uchar>(i);
for (int j = 2; j < colMax; j++)
{
if (data[j] == 255)
{
addFirst2++;
}
}
if (addFirst2 < addFirstTemp) //篩選最小值所在行
{
row2 = i;
addFirstTemp = addFirst2 + 3;
//cout << "行底" << row2 << endl;
//flag_y = 1;
}
}
int orow;
orow = row2 - row1;
Mat w_image;
Mat rgb_w_image;
w_image = dstImage(Rect(0, row1, colMax, orow));
rgb_w_image = cutImage(Rect(0, row1, colMax, orow));
//namedWindow("裁剪上下圖");
//imshow("裁剪上下圖", w_image);
int rowMax_ALT = w_image.rows - 1; //開區間，防止越界(注意，裁剪完上下後要重新寫行和寬，因為行和寬已經改變)
int colMax_ALT = w_image.cols - 1; //開區間，防止越界（注意，裁剪完上下後要重新寫行和寬，因為行和寬已經改變）
int col_1 = 2;
int col_2 = w_image.cols;
int add = 2;
int add1 = 0;
int add2 = 0;
int addTemp = add; //第一次用時已經改變數值，容易忽略！！！！！
//裁剪左右邊。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。
//左邊
//for (int i = 0; i < colMax_ALT / 18; i++, add1 = 0) // 剛剛好
//{
// for (int j = 2; j < rowMax_ALT; j++)
// {
// data = dstImage.ptr<uchar>(j);
// if (data[i] == 255)
// {
// add1++;
// }
// }
// if (add1 < add) //篩選最小值所在列
// {
// col_1 = i;
// add = add1 + 1;
// }
//}
//右邊
if (specialFlag)
{
for (int i = colMax_ALT; i > colMax_ALT - colMax_ALT / 18; i--, add2 = 0) // 剛剛好
{
for (int j = 2; j < rowMax_ALT; j++)
{
data = dstImage.ptr<uchar>(j);
if (data[i] == 255)
{
add2++;
}
}
if (add2 < addTemp) //篩選最小值所在列
{
col_2 = i;
addTemp = add2 + 1;
//cout << "行底" << row2 << endl;
}
}
}
int o_col;
o_col = col_2 - col_1;
Mat H_image;
H_image = w_image(Rect(col_1, 0, o_col, rowMax_ALT));
rgb_w_image = rgb_w_image(Rect(col_1, 0, o_col, rowMax_ALT));
//namedWindow("再裁剪左右圖");
//imshow("再裁剪左右圖", H_image);
//namedWindow("裁剪後彩圖");
//imshow("裁剪後彩圖", rgb_w_image);
return rgb_w_image;
}
void CharCut(Mat srcImage)
{
resize(srcImage, srcImage, Size(320, 320 * srcImage.rows / srcImage.cols));
//namedWindow("Resize車牌圖");
//imshow("Resize車牌圖", srcImage);
GaussianBlur(srcImage, srcImage, Size(3, 3), 0, 0);
/*namedWindow("GaussianBlur車牌圖");
imshow("GaussianBlur車牌圖", srcImage);
*/
medianBlur(srcImage, srcImage, 3);
//namedWindow("Src_medianBlur圖");
//imshow("Src_medianBlur圖", srcImage);
cvtColor(srcImage, srcImage, CV_BGR2HSV);
//將白色區域二值化
Mat doubleImage;
//inRange(srcImage, Scalar(0, 0, 10), Scalar(180, 75, 255), doubleImage); //增大 S 即飽和度可以使hsv白色檢測範圍更大
inRange(srcImage, Scalar(0, 0, 0), Scalar(180, 125, 245), doubleImage);
namedWindow("doubleImage圖");
imshow("doubleImage圖", doubleImage);
int colTemp = 0;
int rowMax = doubleImage.rows;
int colMax = doubleImage.cols;
int addFirst = 0;
int add = 0;
int k1 = 0;
int k2;
int kTemp = 0;
int times = 0;
int oneCutEnd = 0;
float t = 1.0;
uchar* data;
cout << "Test: " << specialFlag << endl;
//針對巢狀車牌處理
if (specialFlag)
{
for (int i = 2; i < colMax; i++, addFirst = 0, add = 0)
{
for (int j = rowMax / 10.8; j < rowMax - rowMax / (10.8*t); j++)
{
data = doubleImage.ptr<uchar>(j);
if (data[i - 1] == 255)
{
addFirst++; //統計前一列
}
}
for (int j = rowMax / 10.8; j < rowMax - rowMax / (10.8*t); j++)
{
data = doubleImage.ptr<uchar>(j);
if (data[i] == 255)
{
add++; //統計後一列
}
}
//省份字元分開切割
if (!times)
{
if (!oneCutEnd && (!addFirst && add))
k1 = i - 1;
if (addFirst && !add)
{
k2 = i;
oneCutEnd = 1;
if (k2 - k1 > colMax / 11.25)
{
times = 1;
if (k2 - k1 < colMax / 5.625)
SingleCharCut(doubleImage, k1, k2);
else
i = 2;
}
}
} //切割其他字元
else {
if (!addFirst && add)
k1 = i - 1;
if (addFirst && !add)
{
k2 = i;
if (k2 - k1 > colMax / 32)
{
if (k2 - k1 < colMax / 5.625)
SingleCharCut(doubleImage, k1, k2);
else //針對巢狀車牌下部連線過靠上
{
i = k1;
t -= 0.1;
}
}
else
{ //!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!處理中間分割點與‘ 1 '!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
for (int a = k1; a <= k2; a++)
{
data = doubleImage.ptr<uchar>(rowMax / 5);
if (data[a] == 255)
kTemp++;
}
if (kTemp > 0)
SingleCharCut(doubleImage, k1, k2);
kTemp = 0;
}
}
}
}
k2 = colMax;
if (k2 - k1 > colMax / 32)
SingleCharCut(doubleImage, k1, k2);
specialFlag = false;
}
else {
for (int i = 2; i < colMax; i++, addFirst = 0, add = 0)
{
for (int j = rowMax / 12.8; j < rowMax - rowMax / 12.8; j++)
{
data = doubleImage.ptr<uchar>(j);
if (data[i - 1] == 255)
{
addFirst++;
}
}
for (int j = rowMax / 12.8; j < rowMax - rowMax / 12.8; j++)
{
data = doubleImage.ptr<uchar>(j);
if (data[i] == 255)
{
add++;
}
}
if (!times)
{
if (!oneCutEnd && (!addFirst && add))
k1 = i - 1;
if (addFirst && !add)
{
k2 = i;
oneCutEnd = 1;
if (k2 - k1 > colMax / 11.25)
{
times = 1;
if (k2 - k1 < colMax / 5.625)
SingleCharCut(doubleImage, k1, k2);
else
i = 2;
}
}
}
else {
if (!addFirst && add)
k1 = i - 1;
if (addFirst && !add)
{
k2 = i;
if (k2 - k1 > colMax / 32)
SingleCharCut(doubleImage, k1, k2);
else
{ //!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!處理中間分割點與‘ 1 '!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
for (int a = k1; a <= k2; a++)
{
data = doubleImage.ptr<uchar>(rowMax / 5);
if (data[a] == 255)
kTemp++;
}
if (kTemp > 0)
SingleCharCut(doubleImage, k1, k2);
kTemp = 0;
}
}
}
}
}
}
void SingleCharCut(Mat doubleImage, int k1, int k2)
{
//printf("k1 = %d ,k2 = %dn", k1, k2);
int rowMax = doubleImage.rows;
Mat image;
image = doubleImage(Rect(k1, 0, k2 - k1, rowMax));
int row1 = 0;
int row2 = image.rows;
rowMax = image.rows - 1; //開區間，防止越界
int colMax = image.cols; //開區間，防止越界
int addFirst = 2;
int addFirst1 = 0;
int addFirst2 = 0;
uchar* data;
//測中間畫素
//image.at<uchar>(rowMax-1, colMax-1);
//cout << "Width:" << j << endl;
int addFirstTemp = addFirst; //第一次用時已經改變數值，容易忽略！！！！！
//裁剪上下邊。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。
//上邊
for (int i = 0; i < rowMax / 4; i++, addFirst1 = 0) // 6 剛剛好
{
data = image.ptr<uchar>(i);
for (int j = 0; j < colMax; j++)
{
if (data[j] == 255)
{
addFirst1++;
}
}
if (addFirst1 < addFirst) //篩選最小值所在行
{
row1 = i;
addFirst = addFirst1 + 1;
}
}
//下邊
for (int i = rowMax; i > rowMax - rowMax / 4; i--, addFirst2 = 0) // 6 剛剛好
{
data = image.ptr<uchar>(i);
for (int j = 2; j < colMax; j++)
{
if (data[j] == 255)
{
addFirst2++;
}
}
if (addFirst2 < addFirstTemp) //篩選最小值所在行
{
row2 = i;
addFirstTemp = addFirst2 + 1;
}
}
int orow;
orow = row2 - row1;
Mat w_image;
w_image = image(Rect(0, row1, colMax, orow));
singleChar.push_back(w_image);
}
void ShowChar()
{
int length = singleChar.size();
for (int i = 0; i < length; i++) {
resize(singleChar[i], singleChar[i], Size(20, 40)); //字元影象歸一化
//namedWindow(to_string(i) + "圖");
//imshow(to_string(i) + "圖", singleChar[i]);
}
}
//讀取省份模板
struct stu
{
Mat image;
double matchDegree;
};
struct stu first[35];
void readProvince()
{
int i = 0;
//讀取字元
{
first[i].image = imread("match\zw1.bmp", 0);
i++;
first[i].image = imread("match\zw2.bmp", 0);
i++;
first[i].image = imread("match\zw3.bmp", 0);
i++;
first[i].image = imread("match\zw4.bmp", 0);
i++;
first[i].image = imread("match\zw5.bmp", 0);
i++;
first[i].image = imread("match\zw6.bmp", 0);
i++;
first[i].image = imread("match\zw7.bmp", 0);
i++;
first[i].image = imread("match\zw8.bmp", 0);
i++;
first[i].image = imread("match\zw9.bmp", 0);
i++;
first[i].image = imread("match\zw10.bmp", 0);
i++;
first[i].image = imread("match\zw11.bmp", 0);
i++;
first[i].image = imread("match\zw12.bmp", 0);
i++;
first[i].image = imread("match\zw13.bmp", 0);
i++;
first[i].image = imread("match\zw14.bmp", 0);
i++;
first[i].image = imread("match\zw15.bmp", 0);
i++;
first[i].image = imread("match\zw16.bmp", 0);
i++;
first[i].image = imread("match\zw17.bmp", 0);
i++;
first[i].image = imread("match\zw18.bmp", 0);
i++;
first[i].image = imread("match\zw19.bmp", 0);
i++;
first[i].image = imread("match\zw20.bmp", 0);
i++;
first[i].image = imread("match\zw21.bmp", 0);
i++;
first[i].image = imread("match\zw22.bmp", 0);
i++;
first[i].image = imread("match\zw23.bmp", 0);
i++;
first[i].image = imread("match\zw24.bmp", 0);
i++;
first[i].image = imread("match\zw25.bmp", 0);
i++;
first[i].image = imread("match\zw26.bmp", 0);
i++;
first[i].image = imread("match\zw27.bmp", 0);
i++;
first[i].image = imread("match\zw28.bmp", 0);
i++;
first[i].image = imread("match\zw29.bmp", 0);
i++;
first[i].image = imread("match\zw30.bmp", 0);
i++;
first[i].image = imread("match\zw31.bmp", 0);
i++;
first[i].image = imread("match\zw32.bmp", 0);
i++;
first[i].image = imread("match\zw33.bmp", 0);
i++;
first[i].image = imread("match\zw34.bmp", 0);
i++;
first[i].image = imread("match\zw35.bmp", 0);
}
}
//識別省份字元
void MatchProvince()
{
int rowMax = 40;
int colMax = 20;
int add = 0;
int addTemp = 0;
Mat absCutImage;
double temp;
int index = 0;
uchar* data;
for (int i = 0; i < rowMax; i++)
{
data = singleChar[0].ptr<uchar>(i);
for (int j = 0; j < colMax; j++)
{
if (data[j] == 255)
{
add++;
}
}
}
int firstLength = end(first) - begin(first);
//printf("陣列長度1 %dn",firstLength);
for (int x = 0; x < firstLength; x++, addTemp = 0)
{
absCutImage = abs(first[x].image - singleChar[0]);
for (int i = 0; i < rowMax; i++)
{
data = absCutImage.ptr<uchar>(i);
for (int j = 0; j < colMax; j++)
{
if (data[j] == 255)
{
addTemp++;
}
}
}
temp = 1.0 - 1.0*addTemp / add;
if (temp <= 1)
first[x].matchDegree = temp;
else
first[x].matchDegree = 0;
if (x > 0 && first[x].matchDegree > first[index].matchDegree)
index = x;
}
/*absCutImage = abs(singleChar[0] - first[index].image);
namedWindow("省份圖片相減後圖" + to_string(0));
imshow("省份圖片相減後圖" + to_string(0), absCutImage);*/
printf("省份字元最大匹配度： %lfn", first[index].matchDegree);
switch (index) {
case 0:
printf("藏");
carPlateProvince += "藏";
break;
case 1:
printf("川");
carPlateProvince += "川";
break;
case 2:
printf("鄂");
carPlateProvince += "鄂";
break;
case 3:
printf("甘");
carPlateProvince += "甘";
break;
case 4:
printf("贛");
carPlateProvince += "贛";
break;
case 5:
printf("貴");
carPlateProvince += "貴";
break;
case 6:
printf("桂");
carPlateProvince += "桂";
break;
case 7:
printf("黑");
carPlateProvince += "黑";
break;
case 8:
printf("瀘");
carPlateProvince += "瀘";
break;
case 9:
printf("吉");
carPlateProvince += "吉";
break;
case 10:
printf("翼");
carPlateProvince += "翼";
break;
case 11:
printf("津");
carPlateProvince += "津";
break;
case 12:
printf("晉");
carPlateProvince += "晉";
break;
case 13:
printf("京");
carPlateProvince += "京";
break;
case 14:
printf("遼");
carPlateProvince += "遼";
break;
case 15:
printf("魯");
carPlateProvince += "魯";
break;
case 16:
printf("蒙");
carPlateProvince += "蒙";
break;
case 17:
printf("閩");
carPlateProvince += "閩";
break;
case 18:
printf("寧");
carPlateProvince += "寧";
break;
case 19:
printf("青");
carPlateProvince += "青";
break;
case 20:
printf("瓊");
carPlateProvince += "瓊";
break;
case 21:
printf("陝");
carPlateProvince += "陝";
break;
case 22:
printf("蘇");
carPlateProvince += "蘇";
break;
case 23:
printf("皖");
carPlateProvince += "皖";
break;
case 24:
printf("湘");
carPlateProvince += "湘";
break;
case 25:
printf("新");
carPlateProvince += "新";
break;
case 26:
printf("渝");
carPlateProvince += "渝";
break;
case 27:
printf("豫");
carPlateProvince += "豫";
break;
case 28:
printf("粵");
carPlateProvince += "粵";
break;
case 29:
printf("雲");
carPlateProvince += "雲";
break;
case 30:
printf("浙");
carPlateProvince += "浙";
break;
case 31:
printf("湘");
carPlateProvince += "湘";
break;
case 32:
printf("湘");
carPlateProvince += "湘";
break;
case 33:
printf("魯");
carPlateProvince += "魯";
break;
case 34:
printf("粵");
carPlateProvince += "粵";
break;
}
printf("n");
}
//讀取字母和數位模板
struct stu1
{
char number;
Mat image;
double matchDegree;
};
struct stu1 second[49];
void readNumber()
{
for (int i = 0; i < 10; i++) {
second[i].image = imread("match\" + to_string(i) + ".bmp", 0);
second[i].number = 48 + i;
}
//讀取字元
{
int i = 10;
second[i].image = imread("match\6a.bmp", 0);
second[i].number = '6';
i++;
second[i].image = imread("match\3a.bmp", 0);
second[i].number = '3';
i++;
second[i].image = imread("match\P1.bmp", 0);
second[i].number = 'P';
i++;
second[i].image = imread("match\8b.bmp", 0);
second[i].number = '8';
i++;
second[i].image = imread("match\K1.bmp", 0);
second[i].number = 'K';
i++;
second[i].image = imread("match\9a.bmp", 0);
second[i].number = '9';
i++;
second[i].image = imread("match\B2.bmp", 0);
second[i].number = 'B';
i++;
second[i].image = imread("match\G1.bmp", 0);
second[i].number = 'G';
i++;
second[i].image = imread("match\T1.bmp", 0);
second[i].number = 'T';
i++;
second[i].image = imread("match\B1.bmp", 0);
second[i].number = 'B';
i++;
second[i].image = imread("match\8a.bmp", 0);
second[i].number = '8';
i++;
second[i].image = imread("match\1a.bmp", 0);
second[i].number = '1';
i++;
second[i].image = imread("match\7a.bmp", 0);
second[i].number = '7';
i++;
second[i].image = imread("match\D1.bmp", 0);
second[i].number = 'D';
i++;
second[i].image = imread("match\0a.bmp", 0);
second[i].number = '0';
i++;
second[i].image = imread("match\A.bmp", 0);
second[i].number = 'A';
i++;
second[i].image = imread("match\B.bmp", 0);
second[i].number = 'B';
i++;
second[i].image = imread("match\C.bmp", 0);
second[i].number = 'C';
i++;
second[i].image = imread("match\D.bmp", 0);
second[i].number = 'D';
i++;
second[i].image = imread("match\E.bmp", 0);
second[i].number = 'E';
i++;
second[i].image = imread("match\F.bmp", 0);
second[i].number = 'F';
i++;
second[i].image = imread("match\G.bmp", 0);
second[i].number = 'G';
i++;
second[i].image = imread("match\H.bmp", 0);
second[i].number = 'H';
i++;
second[i].image = imread("match\J.bmp", 0);
second[i].number = 'J';
i++;
second[i].image = imread("match\K.bmp", 0);
second[i].number = 'K';
i++;
second[i].image = imread("match\L.bmp", 0);
second[i].number = 'L';
i++;
second[i].image = imread("match\M.bmp", 0);
second[i].number = 'M';
i++;
second[i].image = imread("match\N.bmp", 0);
second[i].number = 'N';
i++;
second[i].image = imread("match\P.bmp", 0);
second[i].number = 'P';
i++;
second[i].image = imread("match\Q.bmp", 0);
second[i].number = 'Q';
i++;
second[i].image = imread("match\R.bmp", 0);
second[i].number = 'R';
i++;
second[i].image = imread("match\S.bmp", 0);
second[i].number = 'S';
i++;
second[i].image = imread("match\T.bmp", 0);
second[i].number = 'T';
i++;
second[i].image = imread("match\U.bmp", 0);
second[i].number = 'U';
i++;
second[i].image = imread("match\V.bmp", 0);
second[i].number = 'V';
i++;
second[i].image = imread("match\W.bmp", 0);
second[i].number = 'W';
i++;
second[i].image = imread("match\X.bmp", 0);
second[i].number = 'X';
i++;
second[i].image = imread("match\Y.bmp", 0);
second[i].number = 'Y';
i++;
second[i].image = imread("match\Z.bmp", 0);
second[i].number = 'Z';
}
}
//識別其他字元
void MatchNumber()
{
int rowMax = 40;
int colMax = 20;
int add = 0;
int addTemp = 0;
Mat absCutImage;
double temp;
int index = 0;
int length = singleChar.size();
int secondLength = end(second) - begin(second);
//printf("陣列長度2 %d n", secondLength);
uchar* data;
int q = 0;
for (int y = 1; y < length; y++, add = 0, index = 0)
{
if (y > 6) //防止多讀
break;
//統計要讀取字元的白色畫素總值
for (int i = 0; i < rowMax; i++)
{
data = singleChar[y].ptr<uchar>(i);
for (int j = 0; j < colMax; j++)
{
if (data[j] == 255)
{
add++;
}
}
}
//逐個字元識別
for (int x = 0; x < secondLength; x++, addTemp = 0)
{
absCutImage = abs(singleChar[y] - second[x].image);
//統計相減之後的影象白色畫素總值
for (int i = 0; i < rowMax; i++)
{
data = absCutImage.ptr<uchar>(i);
for (int j = 0; j < colMax; j++)
{
if (data[j] == 255)
{
addTemp++;
}
}
}
temp = 1.0 - 1.0*addTemp / add;
if (temp <= 1 && temp > 0)
second[x].matchDegree = temp;
else
second[x].matchDegree = 0;
//獲取最大匹配度對應索引index
if (x > 0 && second[x].matchDegree > second[index].matchDegree)
index = x;
}
absCutImage = abs(singleChar[y] - second[index].image);
/* namedWindow("圖片相減後圖"+to_string(y));
imshow("圖片相減後圖" + to_string(y), absCutImage);*/
printf("最大匹配度： %lfn", second[index].matchDegree);
printf("對應字元： %cn", second[index].number);
test[q] = second[index].number;
//printf("ntest11111 %cn", test[q]);
q++;
}
test[q] = ' ';
//printf("ntest22222 %cn", test[q-1]);
//cout<< "xxxxxxxxxxxxxx"<<carPlate<<endl;
}
void VideoShow(Mat videoImage)
{
/*if(videoFlag==0)*/
//carPlate = "京A J9846";
carPlate += test;
carPlateProvince += carPlate;
/*carPlate.copy(test,strlen(test));*/
cout << carPlateProvince << endl;
cout << carPlateProvince.length() << endl;
if(carPlateProvince.length()<10)
putTextZH(videoImage, "Not Plate!", Point(490, 20), Scalar(0, 0, 255), 30, "Arial", false, false);
else
putTextZH(videoImage, carPlateProvince.c_str(), Point(490, 20), Scalar(0, 0, 255), 30, "Arial", false, false);
/*else if(videoFlag==1)*/
namedWindow("提取車牌結果圖");
imshow("提取車牌結果圖", videoImage);
carPlateProvince = " ";
carPlate = " ";
}
void GetStringSize(HDC hDC, const char* str, int* w, int* h)
{
SIZE size;
GetTextExtentPoint32A(hDC, str, strlen(str), &size);
if (w != 0) *w = size.cx;
if (h != 0) *h = size.cy;
}
void putTextZH(Mat &dst, const char* str, Point org, Scalar color, int fontSize, const char* fn, bool italic, bool underline)
{
CV_Assert(dst.data != 0 && (dst.channels() == 1 || dst.channels() == 3));
int x, y, r, b;
if (org.x > dst.cols || org.y > dst.rows) return;
x = org.x < 0 ? -org.x : 0;
y = org.y < 0 ? -org.y : 0;
LOGFONTA lf;
lf.lfHeight = -fontSize;
lf.lfWidth = 0;
lf.lfEscapement = 0;
lf.lfOrientation = 0;
lf.lfWeight = 5;
lf.lfItalic = italic; //斜體
lf.lfUnderline = underline; //下劃線
lf.lfStrikeOut = 0;
lf.lfCharSet = DEFAULT_CHARSET;
lf.lfOutPrecision = 0;
lf.lfClipPrecision = 0;
lf.lfQuality = PROOF_QUALITY;
lf.lfPitchAndFamily = 0;
strcpy_s(lf.lfFaceName, fn);
HFONT hf = CreateFontIndirectA(&lf);
HDC hDC = CreateCompatibleDC(0);
HFONT hOldFont = (HFONT)SelectObject(hDC, hf);
int strBaseW = 0, strBaseH = 0;
int singleRow = 0;
char buf[1 << 12];
strcpy_s(buf, str);
char *bufT[1 << 12]; // 這個用於分隔字串後剩餘的字元，可能會超出。
//處理多行
{
int nnh = 0;
int cw, ch;
const char* ln = strtok_s(buf, "n", bufT);
while (ln != 0)
{
GetStringSize(hDC, ln, &cw, &ch);
strBaseW = max(strBaseW, cw);
strBaseH = max(strBaseH, ch);
ln = strtok_s(0, "n", bufT);
nnh++;
}
singleRow = strBaseH;
strBaseH *= nnh;
}
if (org.x + strBaseW < 0 || org.y + strBaseH < 0)
{
SelectObject(hDC, hOldFont);
DeleteObject(hf);
DeleteObject(hDC);
return;
}
r = org.x + strBaseW > dst.cols ? dst.cols - org.x - 1 : strBaseW - 1;
b = org.y + strBaseH > dst.rows ? dst.rows - org.y - 1 : strBaseH - 1;
org.x = org.x < 0 ? 0 : org.x;
org.y = org.y < 0 ? 0 : org.y;
BITMAPINFO bmp = { 0 };
BITMAPINFOHEADER& bih = bmp.bmiHeader;
int strDrawLineStep = strBaseW * 3 % 4 == 0 ? strBaseW * 3 : (strBaseW * 3 + 4 - ((strBaseW * 3) % 4));
bih.biSize = sizeof(BITMAPINFOHEADER);
bih.biWidth = strBaseW;
bih.biHeight = strBaseH;
bih.biPlanes = 1;
bih.biBitCount = 24;
bih.biCompression = BI_RGB;
bih.biSizeImage = strBaseH * strDrawLineStep;
bih.biClrUsed = 0;
bih.biClrImportant = 0;
void* pDibData = 0;
HBITMAP hBmp = CreateDIBSection(hDC, &bmp, DIB_RGB_COLORS, &pDibData, 0, 0);
CV_Assert(pDibData != 0);
HBITMAP hOldBmp = (HBITMAP)SelectObject(hDC, hBmp);
//color.val[2], color.val[1], color.val[0]
SetTextColor(hDC, RGB(255, 255, 255));
SetBkColor(hDC, 0);
//SetStretchBltMode(hDC, COLORONCOLOR);
strcpy_s(buf, str);
const char* ln = strtok_s(buf, "n", bufT);
int outTextY = 0;
while (ln != 0)
{
TextOutA(hDC, 0, outTextY, ln, strlen(ln));
outTextY += singleRow;
ln = strtok_s(0, "n", bufT);
}
uchar* dstData = (uchar*)dst.data;
int dstStep = dst.step / sizeof(dstData[0]);
unsigned char* pImg = (unsigned char*)dst.data + org.x * dst.channels() + org.y * dstStep;
unsigned char* pStr = (unsigned char*)pDibData + x * 3;
for (int tty = y; tty <= b; ++tty)
{
unsigned char* subImg = pImg + (tty - y) * dstStep;
unsigned char* subStr = pStr + (strBaseH - tty - 1) * strDrawLineStep;
for (int ttx = x; ttx <= r; ++ttx)
{
for (int n = 0; n < dst.channels(); ++n) {
double vtxt = subStr[n] / 255.0;
int cvv = vtxt * color.val[n] + (1 - vtxt) * subImg[n];
subImg[n] = cvv > 255 ? 255 : (cvv < 0 ? 0 : cvv);
}
subStr += 3;
subImg += dst.channels();
}
}
SelectObject(hDC, hOldBmp);
SelectObject(hDC, hOldFont);
DeleteObject(hf);
DeleteObject(hBmp);
DeleteDC(hDC);
}以上就是本文的全部內容，希望對大家的學習有所幫助，也希望大家多多支援it145.com。
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2021-06-01 09:31:24
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有哪些事是買了雪佛蘭後才知道的？美事偷著樂，開拓者車主隨聊
开拓者的车机是兼容苹果和<em>安卓</em>，虽然我不怎么用，但确实兼顾了我家人的很多需求：副驾的门板还配有解锁开关，有的时候老婆开车，下车的时候偶尔会忘记解锁，我在副驾驶可以自己开门：第二排设计很好，不仅配置了一个很大的
2021-06-01 09:30:48
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iPhone12在618最新定價，跌價幅度超過1400元，還等iPhone13嗎？
不仅是<em>安卓</em>手机，苹果手机的降价力度也是前所未有了，iPhone12也“跳水价”了，发布价是6799元，如今已经跌至5308元，降价幅度超过1400元，最新定价确认了。iPhone12是苹果首款5G手机，同时也是全球首款5nm芯片的智能机，它
2021-06-01 09:30:45