基于opencv的手勢識別（轉(zhuǎn)）

horse_home 2014-04-15

展開全文

OpenCV模板匹配的方法識別手勢（修改版）

找不原出處。

//修改后能運行的程序，但是結果好像不是很好

//我的機子是賽揚600，超頻到900在用，內(nèi)存是256sdram，剛才調(diào)的時候居然

//內(nèi)存不夠用了，又很多地方需要改進，如果有時間，我會把改了的重新上傳

//還有個問題就是，偶爾會定位到我的臉上，估計是我的臉長的太像手了 : )

//采用模板匹配的方法識別手勢

//這次修改了內(nèi)存消耗猛增的bug，但是仍然有小幅增長，只要測試時間在半個

//小時之內(nèi)，一般不會出現(xiàn)內(nèi)存不足的提示。

//修正了原來版本在讀取10幅圖后顯示錯誤的問題

//測試圖片請在《[資料]OpenCV模板匹配的方法識別手勢》里面下載

#ifdef _CH_

#define WIN32

#error "The file needs cvaux, which is not wrapped yet. Sorry"

#endif

#ifndef _EiC

#include "cv.h"

#include "cxcore.h"

#include "cvaux.h"

#include "highgui.h"

#include <stdio.h>

#include <stdlib.h>

#include <string.h>

#include <assert.h>

#include <math.h>

#include <float.h>

#include <limits.h>

#include <time.h>

#include <ctype.h>

#endif

static CvMemStorage* storage;

//static double color;

static CvSize imgSize;

static CvSize tmplSize;

static CvSeq* contour;

static CvSeq* biggest;

static CvCapture* capture = 0;

static int isHandOpen = 1;

//static double color;

static CvScalar color;

static IplImage *img;

static IplImage *tmpImg;

static IplImage *conv;

static IplImage *H;

static IplImage *S;

static IplImage *V;

static IplImage *tmpH1;

static IplImage *tmpS1;

static IplImage *tmpH2;

static IplImage *tmpS2;

static IplImage *tmpH3;

static IplImage *tmpS3;

static IplImage *openHandTmpl, *closedHandTmpl;

static IplImage *openGrayHandTmpl, *closedGrayHandTmpl;

static IplImage *openscaledTmpl, *closedscaledTmpl;

static IplImage *openMatchResult, *closedMatchResult;

FILE *output;

void handDetect( IplImage *img);

static int numImg = 10;

char *names[] = { "./images/test01.jpg", "./images/test02.jpg", "./images/test03.jpg", "./images/test04.jpg", "./images/test05.jpg",

"../images/test06.jpg", "./images/test07.jpg", "./images/test08.jpg", "./images/test09.jpg", "./images/test10.jpg"};

char *resultsiamge[] = {"result01.jpg","result02.jpg","result03.jpg","result04.jpg","result05.jpg","result06.jpg","result07.jpg",

"result08.jpg","result09.jpg","result10.jpg"};

int main( int argc, char** argv )

{

int i = 0;

char filename[80];

storage = cvCreateMemStorage(0);

#ifdef DEBUG

cvNamedWindow( "Template1", 1 );

cvNamedWindow( "Template2", 1 );

cvNamedWindow( "Comp Results1", 1 );

cvNamedWindow( "Comp Results2", 1 );

cvNamedWindow( "Skin Detection", 1 );

#endif

openHandTmpl = cvLoadImage("openHandTmpl.jpg",1);

closedHandTmpl = cvLoadImage("closedHandTmpl.jpg",1);

// Convert form RGB to GRAY

tmplSize.width = openHandTmpl->width;

tmplSize.height = openHandTmpl->height;

openGrayHandTmpl = cvCreateImage( tmplSize, IPL_DEPTH_8U, 1);

cvCvtColor( openHandTmpl, openGrayHandTmpl, CV_BGR2GRAY );

tmplSize.width = closedHandTmpl->width;

tmplSize.height = closedHandTmpl->height;

closedGrayHandTmpl = cvCreateImage( tmplSize, IPL_DEPTH_8U, 1);

cvCvtColor( closedHandTmpl, closedGrayHandTmpl, CV_BGR2GRAY );

cvNamedWindow("source",1);

cvMoveWindow("source",0,0);

cvNamedWindow( "Results", 1 );

cvMoveWindow("Results",400,300);

cvAddSearchPath("\\images\\");

// Open the Output File

output = fopen( "results.log", "w" );

// Color for contour drawing

color = CV_RGB( 255,255,255 );

if( argc == 1 || (argc == 2 && strlen(argv[1]) == 1 && isdigit(argv[1][0])))

{

capture = cvCaptureFromCAM( argc == 2 ? argv[1][0] - '0' : 0 );

}

else if( argc == 2 )

{

capture = cvCaptureFromAVI( argv[1] );

}

if(capture != 0)

{

for(;;)

{

IplImage *frame;//, *frame_copy;

if( !cvGrabFrame( capture ))

break;

frame = cvRetrieveFrame( capture );

if( !frame )

break;

imgSize.width = frame->width;

imgSize.height = frame->height;

// frame_copy = cvCloneImage( frame );

handDetect( frame );

if( cvWaitKey( 10 ) >= 0 )

break;

}

cvReleaseCapture( &capture );

}

else

{

for ( i = 0; i < numImg; i++ )

{

fprintf(output, "Image %i %s ************************\n", i+1, names);

strcpy(filename, "result_");

// cvNamedWindow( names, 1 );

// cvNamedWindow("source",1);

// cvMoveWindow("source",0,0);

img = cvLoadImage(names,1);

cvShowImage("source",img);

cvWaitKey(0);

if( img )

{

imgSize.width = img->width;

imgSize.height = img->height;

handDetect( img );

// strcat(filename, names);

cvSaveImage(resultsiamge, img);

cvReleaseImage(&img);

}

cvWaitKey(0);

// for ( i = 0; i < numImg; i++ )

// {

// cvDestroyWindow( names);

// }

}

cvReleaseImage(&tmpImg);

cvReleaseImage(&conv);

cvReleaseImage(&H);

cvReleaseImage(&S);

cvReleaseImage(&V);

cvReleaseImage(&tmpH1);

cvReleaseImage(&tmpH2);

cvReleaseImage(&tmpH3);

cvReleaseImage(&tmpS1);

cvReleaseImage(&tmpS2);

cvReleaseImage(&tmpS3);

cvReleaseImage(&openHandTmpl);

cvReleaseImage(&closedHandTmpl);

cvReleaseImage(&openGrayHandTmpl);

cvReleaseImage(&closedGrayHandTmpl);

cvReleaseImage(&openscaledTmpl);

cvReleaseImage(&closedscaledTmpl);

cvReleaseImage(&openMatchResult);

cvReleaseImage(&closedMatchResult);

cvReleaseMemStorage(&storage);

fclose( output );

// cvDestroyWindow( "Result");

#ifdef DEBUG

cvDestroyWindow( "Template1");

cvDestroyWindow( "Template2" );

cvDestroyWindow( "Comp Results1" );

cvDestroyWindow( "Comp Results2" );

cvDestroyWindow( "Skin Detection" );

#endif

return 0;

}

void handDetect( IplImage *img)

{

// CvSize tmplSize;

CvSize resultSize;

IplConvKernel *erosionElement, *dilationElement;

double contArea, imgArea, maxRatio = 0.0;

CvRect bndRect = cvRect(0,0,0,0);

CvPoint pt1, pt2;

float scaleFactor;

CvScalar averageValue;

int startCount = 0;

int openCount = 0;

int closedCount = 0;

float openCompRatio = 0.0;

float closedCompRatio = 0.0;

float bestRatio = 0.0;

imgArea = imgSize.width * imgSize.height;

// Open Template files

// openHandTmpl = cvLoadImage("openHandTmpl.jpg",1);

// closedHandTmpl = cvLoadImage("closedHandTmpl.jpg",1);

// // Convert form RGB to GRAY

// tmplSize.width = openHandTmpl->width;

// tmplSize.height = openHandTmpl->height;

// openGrayHandTmpl = cvCreateImage( tmplSize, IPL_DEPTH_8U, 1);

// cvCvtColor( openHandTmpl, openGrayHandTmpl, CV_BGR2GRAY );

// tmplSize.width = closedHandTmpl->width;

// tmplSize.height = closedHandTmpl->height;

// closedGrayHandTmpl = cvCreateImage( tmplSize, IPL_DEPTH_8U, 1);

// cvCvtColor( closedHandTmpl, closedGrayHandTmpl, CV_BGR2GRAY );

// Generate processing images

tmpImg = cvCloneImage(img);

conv = cvCreateImage( imgSize, IPL_DEPTH_8U, 3);

tmpH1 = cvCreateImage( imgSize, IPL_DEPTH_8U, 1);

tmpS1 = cvCreateImage( imgSize, IPL_DEPTH_8U, 1);

tmpH2 = cvCreateImage( imgSize, IPL_DEPTH_8U, 1);

tmpS2 = cvCreateImage( imgSize, IPL_DEPTH_8U, 1);

tmpH3 = cvCreateImage( imgSize, IPL_DEPTH_8U, 1);

tmpS3 = cvCreateImage( imgSize, IPL_DEPTH_8U, 1);

H = cvCreateImage( imgSize, IPL_DEPTH_8U, 1);

S = cvCreateImage( imgSize, IPL_DEPTH_8U, 1);

V = cvCreateImage( imgSize, IPL_DEPTH_8U, 1);

// Flip the image if in capture mode

if ( capture )

{

cvFlip(conv, conv, 0);

}

// Image Smoothing

//cvSmooth(img,tmpImg,CV_BLUR,3,3);

cvSmooth(img,img,CV_GAUSSIAN,3,3);

// Convert to HSV

cvCvtColor( tmpImg, conv, CV_BGR2HSV );

// Split to HSV planes

cvCvtPixToPlane(conv,H,S,V,0);

// Average Illumination

averageValue = cvAvg( V , 0);

fprintf(output, "Illumination Level = %f\n", averageValue.val[0]);

// Detect skin tone Hues and Saturations

// NOTE: Hue values need to be doubled for actual

// Red to Orange Hue with High Saturation

// Hue 0 to 28 degree and Sat 190 to 200

cvInRangeS(H,cvScalar(0.0,0.0,0,0),cvScalar(14.0,0.0,0,0),tmpH1);

cvInRangeS(S,cvScalar(75.0,0.0,0,0),cvScalar(200.,0.0,0,0),tmpS1);

cvAnd(tmpH1,tmpS1,tmpH1,0);

// Red Hue with Low Saturation

// Hue 0 to 26 degree and Sat 20 to 90

cvInRangeS(H,cvScalar(0.0,0.0,0,0),cvScalar(13.0,0.0,0,0),tmpH2);

cvInRangeS(S,cvScalar(20.0,0.0,0,0),cvScalar(90.0,0.0,0,0),tmpS2);

cvAnd(tmpH2,tmpS2,tmpH2,0);

// Red Hue to Pink with Low Saturation

// Hue 340 to 360 degree and Sat 15 to 90

cvInRangeS(H,cvScalar(170.0,0.0,0,0),cvScalar(180.0,0.0,0,0),tmpH3);

cvInRangeS(S,cvScalar(15.0,0.0,0,0),cvScalar(90.,0.0,0,0),tmpS3);

cvAnd(tmpH3,tmpS3,tmpH3,0);

// Combine the Hue and Sat detections

cvOr(tmpH3,tmpH2,tmpH2,0);

cvOr(tmpH1,tmpH2,tmpH1,0);

// Dilation and Erosion

// Structuring Element Generation

dilationElement = cvCreateStructuringElementEx( 5,5,3,3, CV_SHAPE_RECT , 0 );

erosionElement = cvCreateStructuringElementEx( 5,5,3,3, CV_SHAPE_RECT , 0 );

// Dilation adds a layer on, and returns things to the correct size.

cvDilate(tmpH1,tmpH2,dilationElement,1);

// Erosion peels a layer of pixels off, and makes small regions disappear

cvErode(tmpH1,tmpH3,erosionElement,1);

// Find the contours of all remaining objects

contour = 0;

biggest = 0;

cvFindContours( tmpH3, storage, &contour, sizeof(CvContour), CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE );

cvZero(tmpH1);

// contour now contains a CvSequence of all of the contours

for( ; contour != 0; contour = contour->h_next )

{

contArea = fabs(cvContourArea( contour, CV_WHOLE_SEQ ));

// Ignore very small contours

if ( contArea/imgArea >= 0.015 )

{

cvDrawContours( tmpH1, contour, color, color, 0, -1, 8 );

bndRect = cvBoundingRect( contour, 0 );

// Scale the templates and result images

scaleFactor = ((float)bndRect.width / (float)openHandTmpl->width);

tmplSize.width = scaleFactor * openHandTmpl->width;

tmplSize.height = scaleFactor * openHandTmpl->height;

openscaledTmpl = cvCreateImage( tmplSize, IPL_DEPTH_8U, 1);

closedscaledTmpl = cvCreateImage( tmplSize, IPL_DEPTH_8U, 1);

openMatchResult = cvCreateImage( tmplSize, IPL_DEPTH_8U, 1);

closedMatchResult = cvCreateImage( tmplSize, IPL_DEPTH_8U, 1);

cvResize( openGrayHandTmpl,openscaledTmpl, CV_INTER_LINEAR );

cvResize( closedGrayHandTmpl,closedscaledTmpl, CV_INTER_LINEAR );

// Set ROI for image

bndRect.width = tmplSize.width;

bndRect.height = tmplSize.height;

cvSetImageROI(tmpH1, bndRect);

// Check that ROI matches the tmplate sizes

// If the ROI is too near the edge og the image then the

// ROI may be truncated when it is set and will not match the bndRect

if ( tmpH1->roi->width != bndRect.width || tmpH1->roi->height != bndRect.height )

{

}

else

{

// Compare the Templates to the image ROI

cvCmp( tmpH1,openscaledTmpl, openMatchResult, CV_CMP_EQ );

cvCmp( tmpH1,closedscaledTmpl, closedMatchResult, CV_CMP_EQ );

}

// Analyze the results

startCount = cvCountNonZero( tmpH1 );

openCount = cvCountNonZero( openMatchResult );

closedCount = cvCountNonZero( closedMatchResult );

openCompRatio = (float)openCount/(float)startCount;

closedCompRatio = (float)closedCount/(float)startCount;

bestRatio = 0.0;

// Small regions may give eroneous results

if ( openCompRatio > 1.0 ) openCompRatio = 0.0;

if ( closedCompRatio > 1.0 ) closedCompRatio = 0.0;

// Compare the Open and closed hand results

if ( openCompRatio > closedCompRatio )

{

if ( openCompRatio > maxRatio )

{

maxRatio = openCompRatio;

biggest = contour;

isHandOpen = 1;

}

else

{

if ( closedCompRatio > maxRatio )

{

maxRatio = closedCompRatio;

biggest = contour;

isHandOpen = 0;

}

// Reset ROI

cvResetImageROI( tmpH1 );

// Output the results

fprintf(output, "Contour Non-zero Count = %i\n", startCount);

fprintf(output, "Open Hand Matched Non-zero Count = %i Open Hand Ratio = %f\n", openCount, openCompRatio);

fprintf(output, "Clased Hand Matched Non-zero Count = %i Clased Hand Ratio = %f\n\n", closedCount, closedCompRatio);

#ifdef DEBUG

cvShowImage("Comp Results1",openMatchResult);

cvShowImage("Comp Results2",closedMatchResult);

cvShowImage("Template1",openscaledTmpl);

cvShowImage("Template2",closedscaledTmpl);

cvShowImage("Skin Detection",tmpH1);

cvWaitKey(0);

#endif

}

cvZero(tmpH1);

}

// Draw Detection Rectangle

// Red for Open Hand

// Green for Closed Hand

if ( biggest && maxRatio > 0.60 )

{

bndRect = cvBoundingRect( biggest, 0 );

cvResetImageROI( img );

pt1.x = bndRect.x;

pt1.y = bndRect.y;

pt2.x = bndRect.x + bndRect.width;

pt2.y = bndRect.y + bndRect.height;

if ( isHandOpen )

{

cvRectangle( img, pt1, pt2, CV_RGB(255,0,0), 5 );

}

else

{

cvRectangle( img, pt1, pt2, CV_RGB(0,255,0), 5 );

}

// Display the results

cvShowImage("Results",img);

cvWaitKey(0);

// If we found any contours then free the memory they use.

if (contour!=NULL)

{

cvClearSeq(contour);

}

cvClearMemStorage(storage);

cvReleaseImage(&tmpImg);

cvReleaseImage(&conv);

cvReleaseImage(&tmpH1);

cvReleaseImage(&tmpS1);

cvReleaseImage(&tmpH2);

cvReleaseImage(&tmpS2);

cvReleaseImage(&tmpH3);

cvReleaseImage(&tmpS3);

cvReleaseImage(&H);

cvReleaseImage(&S);

cvReleaseImage(&V);

cvReleaseImage(&openscaledTmpl);

cvReleaseImage(&closedscaledTmpl);

cvReleaseImage(&openMatchResult);

cvReleaseImage(&closedMatchResult);

}

#ifdef _EiC

main(1,"HandDetect.c");

#endif

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基于opencv的手勢識別（轉(zhuǎn)）