简单的验证码识别（opecv）

  1 #include<opencv2/opencv.hpp>
  2 
  3 #include <iostream>  
  4 #include <string>
  5 
  6 struct DataBase{
  7    int  value;        //库特征对应的值
  8    vector<Mat> sample;   //特征库
  9    DataBase(int var , Mat & sam){
 10        value = var;
 11        sample.push_back(sam);
 12    }
 13 };
 14 
 15 typedef struct DataBase dataBase;
 16 
 17 
 18 
 19 
 20 //加载图片
 21 bool loadImage(Mat &src , Mat &gray ,String &filename){
 22 
 23     Mat cbgray ; //合成后图像
 24     int chans;    //bgR分量
 25     src = imread( filename , true ); 
 26     if( src.empty() )    return false;
 27     chans = src.channels();
 28     vector<Mat> bgR(  chans ) ;
 29     //分割通道
 30     split(src,bgR);
 31     //直方图均衡化
 32     for(int chan=0 ; chan < chans ; ++chan ){
 33         equalizeHist(bgR[chan] , bgR[chan]);
 34     }
 35     //单通道合并
 36     merge(bgR , cbgray );
 37     //灰度化
 38     cvtColor(cbgray ,gray ,CV_RGB2GRAY);
 39     return true ;
 40 }
 41 
 42 //二值化
 43 bool binImage(Mat& src , Mat& dst , int _size , int lparam  ,int mediansize){
 44    //采用自适应二值化
 45     adaptiveThreshold(src,src,255,CV_ADAPTIVE_THRESH_MEAN_C,CV_THRESH_BINARY,_size , lparam);
 46    //中值滤波
 47     medianBlur(src,dst,mediansize);
 48    return true;
 49 }
 50 
 51 //装载特征库
 52 /*通常来说这个应该是预先被加载好,以数据库或者其他的形式保存起来
 53   在这地方由于东西比较少，直接现场处理
 54 */
 55 int loadProperty(vector<dataBase> &db  ,int index[]
 56     , int _size = 31 , int lparam = 7 , int mediansize = 3 ){
 57 
 58       //固定路径
 59      char filename[30];
 60      
 61     for(int i=0; i<20 ; ++i){
 62          sprintf(filename,"D:\yzm\tzk\%d.png",index[i]);
 63          Mat tmp;
 64          String path =filename;
 65          loadImage(tmp,tmp,path);    //装载并灰度化 
 66          binImage(tmp,tmp,_size,lparam,mediansize);   //二值化
 67         //imshow("sample",tmp);
 68         //waitKey(0);
 69          db.push_back( dataBase( index[i]%10 , tmp ) );         
 70      }
 71 
 72   return true;
 73 }
 74 
 75 
 76 //对于模块进行匹配
 77 int StartMatch(Mat src , vector< dataBase > db , Point  &curpx){
 78  
 79     int res ;
 80     double maxValue , minValue ,resValue ;
 81     Point  minloc , maxloc ,resloc;
 82 
 83     vector< dataBase >::iterator it;
 84     vector< Mat >::iterator m_it;
 85     
 86     Mat sample ,result;
 87     int curcols , currows;
 88     resValue =1.;
 89 
 90   for( it = db.begin() ; it !=db.end() ; it++ ){
 91 
 92      for( m_it = it->sample.begin() ; m_it != it->sample.end() ; m_it++ ){
 93 
 94           sample = *m_it;
 95           int res_rows = src.rows - sample.rows + 1 ;
 96           int res_cols = src.cols - sample.cols + 1 ;
 97           if( res_rows < 1 || res_cols< 1 ) break;
 98           result = cv::cvarrToMat(cvCreateImage(cvSize(res_cols, res_rows), 1, 1)); 
 99           
100           matchTemplate(src, sample , result ,CV_TM_SQDIFF_NORMED);  //模板匹配算法,平方差匹配
101           
102           minMaxLoc(result, &minValue, &maxValue, &minloc, &maxloc,Mat() );
103           if(resValue > minValue){
104               resValue = minValue;
105               resloc = minloc;
106               res = it->value; //记录这个值的大小
107               curcols = sample.cols;
108               currows = sample.rows;
109          }
110    }
111  }
112  
113 //  rectangle(srcResult, matchLoc, cvPoint(matchLoc.x + curtemplatW, matchLoc.y+ curtemplatH), cvScalar(0,0,255));
114   //设定一个阈值
115   if(resValue<0.2){
116    //++curpx.x;
117     curpx.x += resloc.x + curcols/2.; 
118     rectangle(src,resloc,cvPoint(resloc.x + curcols , resloc.y + currows ),cvScalar(0,0,255));
119   }
120   else{
121       ++curpx.x;
122      res=-1;
123    }
124   return res;
125 }
126 
127 //逐步的扫描
128 vector< int > ScanImage( Mat &src  , vector< dataBase > db , int window_width=12 ,int  window_height=12 ){
129  
130     Point srcp;
131 
132     window_height = src.rows;
133     vector< int > ans ; 
134     while(srcp.x<src.cols){
135 
136      if(srcp.x + window_width > src.cols)
137          window_width = src.cols - srcp.x;
138      Mat tmp = src( Rect(srcp.x,srcp.y,window_width,window_height) );
139 
140      //轮廓检测
141     /* vector< vector <Point> >reg;
142      Mat newtmp = tmp.clone();
143      findContours(newtmp, reg,CV_RETR_EXTERNAL , CV_CHAIN_APPROX_NONE);
144      if( reg.empty() ) break;
145      Rect rect = boundingRect(Mat(reg[0]));
146      Mat ttmp = tmp(rect);
147      imshow("ttmp",ttmp);
148      waitKey(0);*/
149 
150      int ansvalue =StartMatch(tmp,db,srcp);
151      if(ansvalue !=-1){
152       ans.push_back( ansvalue);
153       printf("%d ",ansvalue);
154     }
155   }
156     puts("");
157   return ans;
158 }
159 
160 int main()
161 {
162 
163     Mat check;
164     vector< dataBase > dblist;
165     int dex[20];//{0,1,2,3,4,5,6,7,8,9}; //建立一个索引
166     for(int i=0;i<20 ; dex[i]=i++);
167     loadProperty(dblist,dex,7,33,3);    
168 
169     for(int i=0;i<9;i++)
170   {
171     char path[30];
172 
173     if(i<9)    sprintf(path,"D:/yzm/%d.jpg",i+1);
174     else     sprintf(path,"D:/yzm/%d.png",i-8);
175     
176     loadImage(check,check,String(path));
177     imshow("check",check);
178     waitKey(0);
179 
180     binImage(check,check,17,50,3);
181 
182     ScanImage(check,dblist,11,3);
183     imshow("final",check);
184     waitKey(0);
185     }
186     waitKey(0);
187     return 0;
188 }