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  • 模式识别开发之项目---基于opencv的手势识别

    我使用OpenCV2.4.4的windows版本+Qt4.8.3+VS2010的编译器做了一个手势识别的小程序。

    本程序主要使到了Opencv的特征训练库和最基本的图像处理的知识,包括肤色检测等等。

    废话不多,先看一下基本的界面设计,以及主要功能:

    相信对于Qt有一些了解的人都不会对这个界面的设计感到陌生吧!(该死,该死!)我们向下走:

    紧接着是Qt导入OPenCV2.4.4的库文件:(先看一下Qt的工程文件吧)

    1. #-------------------------------------------------  
    2. #  
    3. # Project created by QtCreator 2013-05-25T11:16:11  
    4. #  
    5. #-------------------------------------------------  
    6.   
    7. QT       += core gui  
    8.   
    9. CONFIG += warn_off  
    10.   
    11. greaterThan(QT_MAJOR_VERSION, 4): QT += widgets  
    12.   
    13. TARGET = HandGesture  
    14. TEMPLATE = app  
    15.   
    16. INCLUDEPATH += E:/MyQtCreator/MyOpenCV/opencv/build/include  
    17.   
    18. SOURCES += main.cpp  
    19.         handgesturedialog.cpp   
    20.     SRC/GestrueInfo.cpp   
    21.     SRC/AIGesture.cpp  
    22.   
    23. HEADERS  += handgesturedialog.h   
    24.     SRC/GestureStruct.h   
    25.     SRC/GestrueInfo.h   
    26.     SRC/AIGesture.h  
    27.   
    28. FORMS    += handgesturedialog.ui  
    29.   
    30. #Load OpenCV runtime libs  
    31. win32:CONFIG(release, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_core244  
    32. else:win32:CONFIG(debug, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_core244d  
    33.   
    34. INCLUDEPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    35. DEPENDPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    36.   
    37. win32:CONFIG(release, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_features2d244  
    38. else:win32:CONFIG(debug, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_features2d244d  
    39.   
    40. INCLUDEPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    41. DEPENDPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    42.   
    43. win32:CONFIG(release, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_haartraining_engine  
    44. else:win32:CONFIG(debug, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_haartraining_engined  
    45.   
    46. INCLUDEPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    47. DEPENDPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    48.   
    49. win32:CONFIG(release, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_highgui244  
    50. else:win32:CONFIG(debug, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_highgui244d  
    51.   
    52. INCLUDEPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    53. DEPENDPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    54.   
    55. win32:CONFIG(release, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_objdetect244  
    56. else:win32:CONFIG(debug, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_objdetect244d  
    57.   
    58. INCLUDEPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    59. DEPENDPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    60.   
    61. win32:CONFIG(release, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_video244  
    62. else:win32:CONFIG(debug, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_video244d  
    63.   
    64. INCLUDEPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    65. DEPENDPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    66.   
    67. win32:CONFIG(release, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_calib3d244  
    68. else:win32:CONFIG(debug, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_calib3d244d  
    69.   
    70. INCLUDEPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    71. DEPENDPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    72.   
    73. win32:CONFIG(release, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_contrib244  
    74. else:win32:CONFIG(debug, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_contrib244d  
    75.   
    76. INCLUDEPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    77. DEPENDPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    78.   
    79. win32:CONFIG(release, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_imgproc244  
    80. else:win32:CONFIG(debug, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_imgproc244d  
    81.   
    82. INCLUDEPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    83. DEPENDPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    84.   
    85.   
    86. win32:CONFIG(release, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_legacy244  
    87. else:win32:CONFIG(debug, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_legacy244d  
    88.   
    89. INCLUDEPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    90. DEPENDPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    91.   
    92. win32:CONFIG(release, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_ml244  
    93. else:win32:CONFIG(debug, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_ml244d  
    94.   
    95. INCLUDEPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    96. DEPENDPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    97.   
    98. win32:CONFIG(release, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_photo244  
    99. else:win32:CONFIG(debug, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_photo244d  
    100.   
    101. INCLUDEPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    102. DEPENDPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    103.   
    104. win32:CONFIG(release, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_nonfree244  
    105. else:win32:CONFIG(debug, debug|release): LIBS += -L$$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10/lib/ -lopencv_nonfree244d  
    106.   
    107. INCLUDEPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  
    108. DEPENDPATH += $$PWD/../../../MyQtCreator/MyOpenCV/opencv/build/x86/vc10  


    当做好以上的基本配置之后,我们进行手势识别的开发:

    第一:要采集到原始的图片

    采集好原始图片后进行修正,包括尺寸大小,那时我还使用到了matlab这个强大的工具,

    紧接着进行图像的样本特征提取,到网上把,CSDN中有大量的关于对图像特征训练库的识别与训练,按照他们一步一步的操作模式不会有问题的饿

    下面是要通过摄像头进行图像的采集,直接贴代码:

    1. void HandGestureDialog::on_pushButton_OpenCamera_clicked()  
    2. {  
    3.     cam = cvCreateCameraCapture(0);  
    4.     timer->start(time_intervals);  
    5.     frame = cvQueryFrame(cam);  
    6.   
    7.     ui->pushButton_OpenCamera->setDisabled (true);  
    8.     ui->pushButton_CloseCamera->setEnabled (true);  
    9.     ui->pushButton_ShowPause->setEnabled (true);  
    10.     ui->pushButton_SnapImage->setEnabled (true);  
    11.     afterSkin = cvCreateImage (cvSize(frame->width,frame->height),IPL_DEPTH_8U,1);  
    12. }  
    1. void HandGestureDialog::readFarme()  
    2. {  
    3.     frame = cvQueryFrame(cam);  
    4.     QImage image((const uchar*)frame->imageData,  
    5.                  frame->width,  
    6.                  frame->height,  
    7.                  QImage::Format_RGB888);  
    8.     image = image.rgbSwapped();  
    9.     image = image.scaled(320,240);  
    10.     ui->label_CameraShow->setPixmap(QPixmap::fromImage(image));  
    11.     gesture.SkinDetect (frame,afterSkin);  
    12.   
    13.     /*next to opencv*/  
    14.   
    15.     if(status_switch == Recongnise)  
    16.     {  
    17.         // Flips the frame into mirror image  
    18.         cvFlip(frame,frame,1);  
    19.   
    20.         // Call the function to detect and draw the hand positions  
    21.         StartRecongizeHand(frame);  
    22.     }  
    23. }  


    查看一下样例图片:

    开始训练的核心代码:

    1. void HandGestureDialog::on_pushButton_StartTrain_clicked()  
    2. {  
    3.     QProgressDialog* process = new QProgressDialog(this);  
    4.     process->setWindowTitle ("Traning Model");  
    5.     process->setLabelText("Processing...");  
    6.     process->setModal(true);  
    7.     process->show ();  
    8.     gesture.setMainUIPointer (this);  
    9.     gesture.Train(process);  
    10.     QMessageBox::about (this,tr("完成"),tr("手势训练模型完成"));  
    11. }  
    1. void CAIGesture::Train(QProgressDialog *pBar)//对指定训练文件夹里面的所有手势进行训练  
    2. {  
    3.     QString curStr = QDir::currentPath ();  
    4.     QString fp1 = "InfoDoc/gestureFeatureFile.yml";  
    5.     fp1 = curStr + "/" + fp1;  
    6.     CvFileStorage *GestureFeature=cvOpenFileStorage(fp1.toStdString ().c_str (),0,CV_STORAGE_WRITE);  
    7.     FILE* fp;  
    8.     QString fp2 = "InfoDoc/gestureFile.txt";  
    9.     fp2 = curStr + "/" + fp2;  
    10.     fp=fopen(fp2.toStdString ().c_str (),"w");  
    11.     int FolderCount=0;  
    12.   
    13.     /*获取当前的目录,然后得到当前的子目录*/  
    14.     QString trainStr = curStr;  
    15.     trainStr += "/TraningSample/";  
    16.     QDir trainDir(trainStr);  
    17.     GestureStruct gesture;  
    18.     QFileInfoList list = trainDir.entryInfoList();  
    19.   
    20.     pBar->setRange(0,list.size ()-2);  
    21.   
    22.   
    23.     for(int i=2;i<list.size ();i++)  
    24.     {  
    25.         pBar->setValue(i-1);  
    26.   
    27.         QFileInfo fileInfo = list.at (i);  
    28.         if(fileInfo.isDir () == true)  
    29.         {  
    30.             FolderCount++;  
    31.   
    32.             QString tempStr = fileInfo.fileName ();  
    33.             fprintf(fp,"%s ",tempStr.toStdString ().c_str ());  
    34.             gesture.angleName = tempStr.toStdString ()+"angleName";  
    35.             gesture.anglechaName = tempStr.toStdString ()+"anglechaName";  
    36.             gesture.countName = tempStr.toStdString ()+"anglecountName";  
    37.   
    38.             tempStr = trainStr + tempStr + "/";  
    39.             QDir subDir(tempStr);  
    40.             OneGestureTrain(subDir,GestureFeature,gesture);  
    41.         }  
    42.     }  
    43.     pBar->autoClose ();  
    44.     delete pBar;  
    45.     pBar = NULL;  
    46.     fprintf(fp,"%s%d","Hand Gesture Number: ",FolderCount);  
    47.     fclose(fp);  
    48.     cvReleaseFileStorage(&GestureFeature);  
    49. }  
    1. void CAIGesture::OneGestureTrain(QDir GestureDir,CvFileStorage *fs,GestureStruct gesture)//对单张图片进行训练  
    2. {     
    3.     IplImage* TrainImage=0;  
    4.     IplImage* dst=0;  
    5.     CvSeq* contour=NULL;  
    6.     CvMemStorage* storage;  
    7.     storage = cvCreateMemStorage(0);  
    8.     CvPoint center=cvPoint(0,0);  
    9.     float radius=0.0;  
    10.     float angle[FeatureNum][10]={0},anglecha[FeatureNum][10]={0},anglesum[FeatureNum][10]={0},anglechasum[FeatureNum][10]={0};  
    11.     float count[FeatureNum]={0},countsum[FeatureNum]={0};  
    12.   
    13.     int FileCount=0;  
    14.     /*读取该目录下的所有jpg文件*/  
    15.     QFileInfoList list = GestureDir.entryInfoList();  
    16.     QString currentDirPath = GestureDir.absolutePath ();  
    17.     currentDirPath += "/";  
    18.     for(int k=2;k<list.size ();k++)  
    19.     {  
    20.         QFileInfo tempInfo = list.at (k);  
    21.         if(tempInfo.isFile () == true)  
    22.         {  
    23.             QString fileNamePath = currentDirPath + tempInfo.fileName ();  
    24.             TrainImage=cvLoadImage(fileNamePath.toStdString ().c_str(),1);  
    25.             if(TrainImage==NULL)  
    26.             {  
    27.                 cout << "can't load image" << endl;  
    28.                 cvReleaseMemStorage(&storage);  
    29.                 cvReleaseImage(&dst);  
    30.                 cvReleaseImage(&TrainImage);  
    31.                 return;  
    32.             }  
    33.             if(dst==NULL&&TrainImage!=NULL)  
    34.                 dst=cvCreateImage(cvGetSize(TrainImage),8,1);  
    35.             SkinDetect(TrainImage,dst);  
    36.             FindBigContour(dst,contour,storage);  
    37.             cvZero(dst);  
    38.             cvDrawContours( dst, contour, CV_RGB(255,255,255),CV_RGB(255,255,255), -1, -1, 8 );  
    39.             ComputeCenter(contour,center,radius);  
    40.   
    41.             GetFeature(dst,center,radius,angle,anglecha,count);  
    42.             for(int j=0;j<FeatureNum;j++)  
    43.             {  
    44.                 countsum[j]+=count[j];  
    45.                 for(int k=0;k<10;k++)  
    46.                 {  
    47.                     anglesum[j][k]+=angle[j][k];  
    48.                     anglechasum[j][k]+=anglecha[j][k];  
    49.                 }  
    50.             }  
    51.             FileCount++;  
    52.             cvReleaseImage(&TrainImage);  
    53.         }  
    54.     }  
    55.     for(int i=0;i<FeatureNum;i++)  
    56.     {  
    57.         gesture.count[i]=countsum[i]/FileCount;  
    58.         for(int j=0;j<10;j++)  
    59.         {  
    60.             gesture.angle[i][j]=anglesum[i][j]/FileCount;  
    61.             gesture.anglecha[i][j]=anglechasum[i][j]/FileCount;  
    62.         }  
    63.     }  
    64.     cvStartWriteStruct(fs,gesture.angleName.c_str (),CV_NODE_SEQ,NULL);//开始写入yml文件  
    65.   
    66.     int i=0;  
    67.     for(i=0;i<FeatureNum;i++)  
    68.         cvWriteRawData(fs,&gesture.angle[i][0],10,"f");//写入肤色角度的值  
    69.   
    70.     cvEndWriteStruct(fs);  
    71.     cvStartWriteStruct(fs,gesture.anglechaName.c_str (),CV_NODE_SEQ,NULL);  
    72.   
    73.     for(i=0;i<FeatureNum;i++)  
    74.         cvWriteRawData(fs,&gesture.anglecha[i][0],10,"f");//写入非肤色角度的值  
    75.   
    76.     cvEndWriteStruct(fs);  
    77.     cvStartWriteStruct(fs,gesture.countName.c_str (),CV_NODE_SEQ,NULL);  
    78.     cvWriteRawData(fs,&gesture.count[0],FeatureNum,"f");//写入肤色角度的个数  
    79.     cvEndWriteStruct(fs);  
    80.   
    81.     cvReleaseMemStorage(&storage);  
    82.     cvReleaseImage(&dst);  
    83. }  
    1. void CAIGesture::SkinDetect(IplImage* src,IplImage* dst)  
    2. {  
    3.     IplImage* hsv = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 3);//use to split to HSV  
    4.     IplImage* tmpH1 = cvCreateImage( cvGetSize(src), IPL_DEPTH_8U, 1);//Use To Skin Detect  
    5.     IplImage* tmpS1 = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1);  
    6.     IplImage* tmpH2 = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1);  
    7.     IplImage* tmpS3 = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1);  
    8.     IplImage* tmpH3 = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1);  
    9.     IplImage* tmpS2 = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1);  
    10.     IplImage* H = cvCreateImage( cvGetSize(src), IPL_DEPTH_8U, 1);  
    11.     IplImage* S = cvCreateImage( cvGetSize(src), IPL_DEPTH_8U, 1);  
    12.     IplImage* V = cvCreateImage( cvGetSize(src), IPL_DEPTH_8U, 1);  
    13.     IplImage* src_tmp1=cvCreateImage(cvGetSize(src),8,3);  
    14.   
    15.     cvSmooth(src,src_tmp1,CV_GAUSSIAN,3,3); //Gaussian Blur  
    16.     cvCvtColor(src_tmp1, hsv, CV_BGR2HSV );//Color Space to Convert  
    17.     cvCvtPixToPlane(hsv,H,S,V,0);//To Split 3 channel  
    18.   
    19.     /*********************Skin Detect**************/  
    20.     cvInRangeS(H,cvScalar(0.0,0.0,0,0),cvScalar(20.0,0.0,0,0),tmpH1);  
    21.     cvInRangeS(S,cvScalar(75.0,0.0,0,0),cvScalar(200.0,0.0,0,0),tmpS1);  
    22.     cvAnd(tmpH1,tmpS1,tmpH1,0);  
    23.   
    24.     // Red Hue with Low Saturation  
    25.     // Hue 0 to 26 degree and Sat 20 to 90  
    26.     cvInRangeS(H,cvScalar(0.0,0.0,0,0),cvScalar(13.0,0.0,0,0),tmpH2);  
    27.     cvInRangeS(S,cvScalar(20.0,0.0,0,0),cvScalar(90.0,0.0,0,0),tmpS2);  
    28.     cvAnd(tmpH2,tmpS2,tmpH2,0);  
    29.   
    30.     // Red Hue to Pink with Low Saturation  
    31.     // Hue 340 to 360 degree and Sat 15 to 90  
    32.     cvInRangeS(H,cvScalar(170.0,0.0,0,0),cvScalar(180.0,0.0,0,0),tmpH3);  
    33.     cvInRangeS(S,cvScalar(15.0,0.0,0,0),cvScalar(90.,0.0,0,0),tmpS3);  
    34.     cvAnd(tmpH3,tmpS3,tmpH3,0);  
    35.   
    36.     // Combine the Hue and Sat detections  
    37.     cvOr(tmpH3,tmpH2,tmpH2,0);  
    38.     cvOr(tmpH1,tmpH2,tmpH1,0);  
    39.   
    40.     cvCopy(tmpH1,dst);  
    41.   
    42.     cvReleaseImage(&hsv);  
    43.     cvReleaseImage(&tmpH1);  
    44.     cvReleaseImage(&tmpS1);  
    45.     cvReleaseImage(&tmpH2);  
    46.     cvReleaseImage(&tmpS2);  
    47.     cvReleaseImage(&tmpH3);  
    48.     cvReleaseImage(&tmpS3);  
    49.     cvReleaseImage(&H);  
    50.     cvReleaseImage(&S);  
    51.     cvReleaseImage(&V);  
    52.     cvReleaseImage(&src_tmp1);  
    53. }  
    1. //To Find The biggest Countour  
    2. void CAIGesture::FindBigContour(IplImage* src,CvSeq* (&contour),CvMemStorage* storage)  
    3. {  
    4.     CvSeq* contour_tmp,*contourPos;  
    5.     int contourcount=cvFindContours(src, storage, &contour_tmp, sizeof(CvContour), CV_RETR_LIST, CV_CHAIN_APPROX_NONE );  
    6.     if(contourcount==0)  
    7.         return;  
    8.     CvRect bndRect = cvRect(0,0,0,0);  
    9.     double contourArea,maxcontArea=0;  
    10.     for( ; contour_tmp != 0; contour_tmp = contour_tmp->h_next )  
    11.     {  
    12.         bndRect = cvBoundingRect( contour_tmp, 0 );  
    13.         contourArea=bndRect.width*bndRect.height;  
    14.         if(contourArea>=maxcontArea)//find Biggest Countour  
    15.         {  
    16.             maxcontArea=contourArea;  
    17.             contourPos=contour_tmp;  
    18.         }  
    19.     }  
    20.     contour=contourPos;  
    21. }  
    1. //Calculate The Center  
    2. void CAIGesture::ComputeCenter(CvSeq* (&contour),CvPoint& center,float& radius)  
    3. {  
    4.     CvMoments m;  
    5.     double M00,X,Y;  
    6.     cvMoments(contour,&m,0);  
    7.     M00=cvGetSpatialMoment(&m,0,0);  
    8.     X=cvGetSpatialMoment(&m,1,0)/M00;  
    9.     Y=cvGetSpatialMoment(&m,0,1)/M00;  
    10.   
    11.     center.x=(int)X;  
    12.     center.y=(int)Y;  
    13.   
    14.     /*******************tO find radius**********************/  
    15.     int hullcount;  
    16.     CvSeq* hull;  
    17.     CvPoint pt;  
    18.     double tmpr1,r=0;  
    19.     hull=cvConvexHull2(contour,0,CV_COUNTER_CLOCKWISE,0);  
    20.     hullcount=hull->total;  
    21.     for(int i=1;i<hullcount;i++)  
    22.     {  
    23.         pt=**CV_GET_SEQ_ELEM(CvPoint*,hull,i);//get each point  
    24.         tmpr1=sqrt((double)((center.x-pt.x)*(center.x-pt.x))+(double)((center.y-pt.y)*(center.y-pt.y)));//计算与中心点的大小  
    25.         if(tmpr1>r)//as the max radius  
    26.             r=tmpr1;  
    27.     }  
    28.     radius=r;  
    29. }  
    1. void CAIGesture::GetFeature(IplImage* src,CvPoint& center,float radius,  
    2.                             float angle[FeatureNum][10],  
    3. float anglecha[FeatureNum][10],  
    4. float count[FeatureNum])  
    5. {  
    6.     int width=src->width;  
    7.     int height=src->height;  
    8.     int step=src->widthStep/sizeof(uchar);  
    9.     uchar* data=(uchar*)src->imageData;  
    10.   
    11.     float R=0.0;  
    12.     int a1,b1,x1,y1,a2,b2,x2,y2;//the distance of the center to other point  
    13.     float angle1_tmp[200]={0},angle2_tmp[200]={0},angle1[50]={0},angle2[50]={0};//temp instance to calculate angule  
    14.     int angle1_tmp_count=0,angle2_tmp_count=0,angle1count=0,angle2count=0,anglecount=0;  
    15.   
    16.     for(int i=0;i<FeatureNum;i++)//分FeatureNum层进行特征提取(也就是5层)分析  
    17.     {  
    18.         R=(i+4)*radius/9;  
    19.         for(int j=0;j<=3600;j++)  
    20.         {  
    21.             if(j<=900)  
    22.             {  
    23.                 a1=(int)(R*sin(j*3.14/1800));//这个要自己实际画一张图就明白了  
    24.                 b1=(int)(R*cos(j*3.14/1800));  
    25.                 x1=center.x-b1;  
    26.                 y1=center.y-a1;  
    27.                 a2=(int)(R*sin((j+1)*3.14/1800));  
    28.                 b2=(int)(R*cos((j+1)*3.14/1800));  
    29.                 x2=center.x-b2;  
    30.                 y2=center.y-a2;  
    31.             }  
    32.             else  
    33.             {  
    34.                 if(j>900&&j<=1800)  
    35.                 {  
    36.                     a1=(int)(R*sin((j-900)*3.14/1800));  
    37.                     b1=(int)(R*cos((j-900)*3.14/1800));  
    38.                     x1=center.x+a1;  
    39.                     y1=center.y-b1;  
    40.                     a2=(int)(R*sin((j+1-900)*3.14/1800));  
    41.                     b2=(int)(R*cos((j+1-900)*3.14/1800));  
    42.                     x2=center.x+a2;  
    43.                     y2=center.y-b2;  
    44.                 }  
    45.                 else  
    46.                 {  
    47.                     if(j>1800&&j<2700)  
    48.                     {  
    49.                         a1=(int)(R*sin((j-1800)*3.14/1800));  
    50.                         b1=(int)(R*cos((j-1800)*3.14/1800));  
    51.                         x1=center.x+b1;  
    52.                         y1=center.y+a1;  
    53.                         a2=(int)(R*sin((j+1-1800)*3.14/1800));  
    54.                         b2=(int)(R*cos((j+1-1800)*3.14/1800));  
    55.                         x2=center.x+b2;  
    56.                         y2=center.y+a2;  
    57.                     }  
    58.                     else  
    59.                     {  
    60.                         a1=(int)(R*sin((j-2700)*3.14/1800));  
    61.                         b1=(int)(R*cos((j-2700)*3.14/1800));  
    62.                         x1=center.x-a1;  
    63.                         y1=center.y+b1;  
    64.                         a2=(int)(R*sin((j+1-2700)*3.14/1800));  
    65.                         b2=(int)(R*cos((j+1-2700)*3.14/1800));  
    66.                         x2=center.x-a2;  
    67.                         y2=center.y+b2;  
    68.                     }  
    69.                 }  
    70.             }  
    71.   
    72.             if(x1>0&&x1<width&&x2>0&&x2<width&&y1>0&&y1<height&&y2>0&&y2<height)  
    73.             {  
    74.                 if((int)data[y1*step+x1]==255&&(int)data[y2*step+x2]==0)  
    75.                 {  
    76.                     angle1_tmp[angle1_tmp_count]=(float)(j*0.1);//从肤色到非肤色的角度  
    77.                     angle1_tmp_count++;  
    78.                 }  
    79.                 else if((int)data[y1*step+x1]==0&&(int)data[y2*step+x2]==255)  
    80.                 {  
    81.                     angle2_tmp[angle2_tmp_count]=(float)(j*0.1);//从非肤色到肤色的角度  
    82.                     angle2_tmp_count++;  
    83.                 }  
    84.             }  
    85.         }  
    86.         int j=0;  
    87.         for(j=0;j<angle1_tmp_count;j++)  
    88.         {  
    89.             if(angle1_tmp[j]-angle1_tmp[j-1]<0.2)//忽略太小的角度  
    90.                 continue;  
    91.             angle1[angle1count]=angle1_tmp[j];  
    92.             angle1count++;  
    93.         }  
    94.   
    95.         for(j=0;j<angle2_tmp_count;j++)  
    96.         {  
    97.             if(angle2_tmp[j]-angle2_tmp[j-1]<0.2)  
    98.                 continue;  
    99.             angle2[angle2count]=angle2_tmp[j];  
    100.             angle2count++;  
    101.         }  
    102.   
    103.         for(j=0;j<max(angle1count,angle2count);j++)  
    104.         {  
    105.             if(angle1[0]>angle2[0])  
    106.             {  
    107.                 if(angle1[j]-angle2[j]<7)//忽略小于7度的角度,因为人的手指一般都大于这个值  
    108.                     continue;  
    109.                 angle[i][anglecount]=(float)((angle1[j]-angle2[j])*0.01);//肤色的角度  
    110.                 anglecha[i][anglecount]=(float)((angle2[j+1]-angle1[j])*0.01);//非肤色的角度,例如手指间的角度  
    111.                 anglecount++;  
    112.             }  
    113.             else  
    114.             {  
    115.                 if(angle1[j+1]-angle2[j]<7)  
    116.                     continue;  
    117.                 anglecount++;  
    118.                 angle[i][anglecount]=(float)((angle1[j+1]-angle2[j])*0.01);  
    119.                 anglecha[i][anglecount]=(float)((angle2[j]-angle1[j])*0.01);  
    120.             }  
    121.         }  
    122.   
    123.         if(angle1[0]<angle2[0])  
    124.             angle[i][0]=(float)((angle1[0]+360-angle2[angle2count-1])*0.01);  
    125.         else  
    126.             anglecha[i][0]=(float)((angle2[0]+360-angle1[angle1count-1])*0.01);  
    127.   
    128.         count[i]=(float)anglecount;  
    129.         angle1_tmp_count=0,angle2_tmp_count=0,angle1count=0,angle2count=0,anglecount=0;  
    130.         for(j=0;j<200;j++)  
    131.         {  
    132.             angle1_tmp[j]=0;  
    133.             angle2_tmp[j]=0;  
    134.         }  
    135.         for(j=0;j<50;j++)  
    136.         {  
    137.             angle1[j]=0;  
    138.             angle2[j]=0;  
    139.         }  
    140.     }  
    141. }  




    基本上对于自己使用代码创建的训练库的特征提取函数和基本的肤色检测和连通域的检测的函数的核心代码都已经贴到上面去了。

    然后再看一下对于特定的手势识别的文件:

    1. void HandGestureDialog::on_pushButton_StartRecongnise_clicked()  
    2. {  
    3.     if(cam==NULL)  
    4.     {  
    5.         QMessageBox::warning (this,tr("Warning"),tr("Please Check Camera !"));  
    6.         return;  
    7.     }  
    8.   
    9.     status_switch = Nothing;  
    10.   
    11.     status_switch = Recongnise;  
    12. }  
    1. void HandGestureDialog::StartRecongizeHand (IplImage *img)  
    2. {  
    3.     // Create a string that contains the exact cascade name  
    4.     // Contains the trained classifer for detecting hand  
    5.     const char *cascade_name="hand.xml";  
    6.     // Create memory for calculations  
    7.     static CvMemStorage* storage = 0;  
    8.     // Create a new Haar classifier  
    9.     static CvHaarClassifierCascade* cascade = 0;  
    10.     // Sets the scale with which the rectangle is drawn with  
    11.     int scale = 1;  
    12.     // Create two points to represent the hand locations  
    13.     CvPoint pt1, pt2;  
    14.     // Looping variable  
    15.     int i;  
    16.     // Load the HaarClassifierCascade  
    17.     cascade = (CvHaarClassifierCascade*)cvLoad( cascade_name, 0, 0, 0 );  
    18.     // Check whether the cascade has loaded successfully. Else report and error and quit  
    19.     if( !cascade )  
    20.     {  
    21.         fprintf( stderr, "ERROR: Could not load classifier cascade " );  
    22.         return;  
    23.     }  
    24.   
    25.     // Allocate the memory storage  
    26.     storage = cvCreateMemStorage(0);  
    27.   
    28.     // Create a new named window with title: result  
    29.     cvNamedWindow( "result", 1 );  
    30.   
    31.     // Clear the memory storage which was used before  
    32.     cvClearMemStorage( storage );  
    33.   
    34.     // Find whether the cascade is loaded, to find the hands. If yes, then:  
    35.     if( cascade )  
    36.     {  
    37.         // There can be more than one hand in an image. So create a growable sequence of hands.  
    38.         // Detect the objects and store them in the sequence  
    39.         CvSeq* hands = cvHaarDetectObjects( img, cascade, storage,  
    40.                                             1.1, 2, CV_HAAR_DO_CANNY_PRUNING,  
    41.                                             cvSize(40, 40) );  
    42.   
    43.         // Loop the number of hands found.  
    44.         for( i = 0; i < (hands ? hands->total : 0); i++ )  
    45.         {  
    46.             // Create a new rectangle for drawing the hand  
    47.             CvRect* r = (CvRect*)cvGetSeqElem( hands, i );  
    48.   
    49.             // Find the dimensions of the hand,and scale it if necessary  
    50.             pt1.x = r->x*scale;  
    51.             pt2.x = (r->x+r->width)*scale;  
    52.             pt1.y = r->y*scale;  
    53.             pt2.y = (r->y+r->height)*scale;  
    54.   
    55.             // Draw the rectangle in the input image  
    56.             cvRectangle( img, pt1, pt2, CV_RGB(230,20,232), 3, 8, 0 );  
    57.         }  
    58.     }  
    59.   
    60.     // Show the image in the window named "result"  
    61.     cvShowImage( "result", img );  
    62.     cvWaitKey (30);  
    63. }  


    注意该特征文件包含了手掌半握式的手势效果较好:

    多谢大家,这么长时间的阅读和浏览,小弟做的很粗糙还有一些地方自已也没有弄明白,希望各位大神批评指教!

    我已把源代码上传到对应的资源中去,以便大家学习修改!

    http://download.csdn.net/detail/liuguiyangnwpu/7467891

    http://blog.csdn.net/berguiliu/article/details/9307495

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  • 原文地址:https://www.cnblogs.com/pengkunfan/p/3947173.html
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