void blur_function(const IplImage *latent_image, IplImage *blur_image, const CvMat *hom1, const CvMat *hom2)
{
const int T = 20;
const int tau = 10;
CvMat *id_mat = cvCreateMat(3, 3, CV_32FC1);
cvSetIdentity(id_mat, cvRealScalar(1));
CvMat *invhom1 = cvCreateMat(3, 3, CV_32FC1);
cvInvert(hom1, invhom1, CV_LU);
CvMat *h1 = cvCreateMat(3, 3, CV_32FC1);
CvMat *h2 = cvCreateMat(3, 3, CV_32FC1);
CvSize size = cvSize(latent_image->width, latent_image->height);
IplImage *temp = cvCreateImage(size, latent_image->depth, latent_image->nChannels);
IplImage *blur = cvCreateImage(size, IPL_DEPTH_32F, latent_image->nChannels);
cvSetZero(blur);
for (int i = 1; i <= tau; ++i)
{
cvAddWeighted(id_mat, (double)(T-i)/T, invhom1, (double)i/T, 0, h1);
cvAddWeighted(id_mat, (double)(T-i)/T, hom2, (double)i/T, 0, h2);
cvWarpPerspective(latent_image, temp, h1, CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS, cvScalarAll(0));
cvAdd(blur, temp, blur, NULL);
cvWarpPerspective(latent_image, temp, h2, CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS, cvScalarAll(0));
cvAdd(blur, temp, blur, NULL);
}
cvAdd(blur, latent_image, blur, NULL);
cvConvertScale(blur, blur_image, 1.0/(2*tau+1), 0);
cvReleaseMat(&id_mat);
cvReleaseMat(&invhom1);
cvReleaseMat(&h1);
cvReleaseMat(&h2);
cvReleaseImage(&temp);
cvReleaseImage(&blur);
}
void ImageProcessorCV::CalculateGradientImageHSV(CByteImage *pInputImage, CByteImage *pOutputImage)
{
if (pInputImage->width != pOutputImage->width || pInputImage->height != pOutputImage->height ||
pInputImage->type != CByteImage::eRGB24 || pOutputImage->type != CByteImage::eGrayScale)
return;
IplImage *pIplInputImage = IplImageAdaptor::Adapt(pInputImage);
IplImage *pIplOutputImage = IplImageAdaptor::Adapt(pOutputImage);
// Determine Gradient Image by Irina Wchter
// instead of normal norm sqrt(x*x +y*y) use |x|+|y| because it is much faster
IplImage *singleChannel0 = cvCreateImage(cvSize(pInputImage->width,pInputImage->height), IPL_DEPTH_8U, 1);
IplImage *singleChannel1 = cvCreateImage(cvSize(pInputImage->width,pInputImage->height), IPL_DEPTH_8U, 1);
IplImage *singleChannel2 = cvCreateImage(cvSize(pInputImage->width,pInputImage->height), IPL_DEPTH_8U, 1);
IplImage *diff = cvCreateImage(cvSize(pInputImage->width, pInputImage->height), IPL_DEPTH_16S, 1);
IplImage *abs = cvCreateImage(cvSize(pInputImage->width, pInputImage->height), IPL_DEPTH_8U, 1);
cvCvtPixToPlane(pIplInputImage, singleChannel0, singleChannel1, singleChannel2, NULL);
// calculate gradients on S-channel
//cvSmooth(singleChannel1, singleChannel1, CV_GAUSSIAN, 3, 3);
cvSobel(singleChannel1, diff, 1, 0, 3);
cvConvertScaleAbs(diff, abs);
cvSobel(singleChannel1, diff, 0, 1, 3);
cvConvertScaleAbs(diff, pIplOutputImage);
cvAdd(abs, pIplOutputImage, pIplOutputImage, 0);
// threshold S-channel for creating a maskfor gradients of H-channel
cvThreshold(singleChannel1, singleChannel1, 60, 255, CV_THRESH_BINARY);
cvDilate(singleChannel1, singleChannel1);
// calculate gradients on H-channel
//cvSmooth(singleChannel0, singleChannel0, CV_GAUSSIAN, 3, 3);
cvSobel(singleChannel0, diff, 1, 0, 3);
cvConvertScaleAbs(diff, abs);
cvSobel(singleChannel0, diff, 0, 1, 3);
cvConvertScaleAbs(diff, singleChannel0);
cvAdd(abs, singleChannel0, singleChannel0, 0);
// filter gradients of H-channel with mask
cvAnd(singleChannel0, singleChannel1, singleChannel0);
// combine to gradient images
cvMax(pIplOutputImage, singleChannel0, pIplOutputImage);
// free memory
cvReleaseImage(&singleChannel0);
cvReleaseImage(&singleChannel1);
cvReleaseImage(&singleChannel2);
cvReleaseImage(&diff);
cvReleaseImage(&abs);
cvReleaseImageHeader(&pIplInputImage);
cvReleaseImageHeader(&pIplOutputImage);
}
void easyplot(IplImage *fr, IplImage *fr0)
{
int rmean = 0.5*(r1+r2), rthick = r1-r2;
CvPoint up, cp, bp;
up.x = coo2pix(upc.x);
up.y = coo2pix(upc.y);
// pause button
if(sqr(pbuttonp.x-up.x)+sqr(pbuttonp.y-up.y)<sqr(r1+buttonr)) {
plot_circular_button(fr, yellow);
}
// user handle
cvCircle(fr, up, rmean, red, rthick+2, CV_AA, 0);
cvCircle(fr, up, rmean, white, rthick-4, CV_AA, 0);
// computer handle
cp.x = coo2pix(cpc.x);
cp.y = coo2pix(cpc.y);
cvCircle(fr, cp, rmean, green, rthick+2, CV_AA, 0);
cvCircle(fr, cp, rmean, white, rthick-4, CV_AA, 0);
// ball
bp.x = coo2pix(bpc.x);
bp.y = coo2pix(bpc.y);
if(bp.y>winy+r0) {
cvCircle(fr, cvPoint(winx/2,winy-bound), criticr, CV_RGB(150,150,150), 10, CV_AA, 0);
cvCircle(fr, cvPoint(winx/2,winy-bound), explosr, CV_RGB(150,150,150), criticr-explosr, CV_AA, 0);
explosr+=7;
}
else if(bp.y<-r0) {
cvCircle(fr, cvPoint(winx/2,bound), criticr, CV_RGB(150,150,150), 10, CV_AA, 0);
cvCircle(fr, cvPoint(winx/2,bound), explosr, CV_RGB(150,150,150), criticr-explosr, CV_AA, 0);
explosr+=7;
}
else {
cvCircle(fr, bp, r0, white, -1, CV_AA, 0);
cvCircle(fr, bp, r0, blue, 3, CV_AA, 0);
}
// blur processing
cvSmooth(fr, fr, CV_BLUR, 15, 15, 0.0, 0.0);
cvAddWeighted(fr0, 0.55, fr, 1.0, -10.0, fr);
// score
cvSetImageROI(fr, scoreroi1);
cvAdd(fr, scoretext1, fr);
cvSetImageROI(fr, scoreroi2);
cvAdd(fr, scoretext2, fr);
cvResetImageROI(fr);
cvSmooth(fr, fr, CV_BLUR, 5, 5, 0.0, 0.0);
cvCopy(fr, fr0);
}
IplImage* stack_imgs( IplImage* img1, IplImage* img2 )
{
IplImage* stacked = cvCreateImage( cvSize( MAX(img1->width, img2->width), img1->height + img2->height ), IPL_DEPTH_8U, 3 );
cvZero( stacked );
cvSetImageROI( stacked, cvRect( 0, 0, img1->width, img1->height ) );
cvAdd( img1, stacked, stacked, NULL );
cvSetImageROI( stacked, cvRect(0, img1->height, img2->width, img2->height) );
cvAdd( img2, stacked, stacked, NULL );
cvResetImageROI( stacked );
// cvShowImage( "stack", stacked );
return stacked;
}
void CueTemplate::adapt() {
if(!m_init) return;
CVImage* cvgrayimg = cvGrayImageIn.getBuffer();
if(!cvgrayimg) { std::cerr<< getName() << "::ERROR::execute()::cvGrayImageIn is NULL!...\n"; return; }
IplImage* grayimg = cvgrayimg->ipl;
TrackData* track = trackIn.getBuffer();
// if(!track){ std::cerr<< getName() << "::ERROR::execute()::trackIn is NULL!...\n"; return; }
float rel;
CvPoint winner;
if(track) {
rel = track->reliability;
winner = track->winnerPos;
}
else{
double min, max;
CvPoint minLoc, maxLoc;
cvMinMaxLoc(mp_boundedoutputimg, &min, &max, &minLoc, &maxLoc, NULL);
rel = (float)max;
winner = maxLoc;
}
if(rel > m_threshold){
// adapt toward new template
int x = winner.x;
int y = winner.y;
if(x < m_halftemplatesizex) x = m_halftemplatesizex;
if(y < m_halftemplatesizey) y = m_halftemplatesizey;
if(x >= grayimg->width - m_halftemplatesizex) x = grayimg->width - m_halftemplatesizex-1;
if(y >= grayimg->height - m_halftemplatesizey) y = grayimg->height - m_halftemplatesizey-1;
CvRect rect;
rect.x = x - m_halftemplatesizex;
rect.y = y - m_halftemplatesizey;
rect.width = m_templatesizex;
rect.height = m_templatesizey;
cvSetImageROI(grayimg, rect );
cvCopy( grayimg, mp_newtemplateimg );
cvScale( mp_templateimg, mp_templateimg, 1.0 - m_tfacs);
cvScale( mp_newtemplateimg, mp_newtemplateimg, m_tfacs);
cvAdd( mp_newtemplateimg, mp_templateimg, mp_templateimg );
cvResetImageROI( grayimg );
cvTemplateImageOut.out();
}
else{
// adapting back to the original template
cvScale( mp_templateimg, mp_templateimg, 1.0 - (m_tfacs/m_back) );
cvScale( mp_origtemplateimg, mp_temptemplateimg, (m_tfacs/m_back) );
cvAdd( mp_temptemplateimg, mp_templateimg, mp_templateimg );
cvTemplateImageOut.out();
}
}
IplImage *stack(IplImage *img1, IplImage *img2) {
IplImage *img = cvCreateImage(cvSize(img1->width + img2->width,
_max(img1->height, img2->height)),
IPL_DEPTH_8U, 3);
cvZero(img);
cvSetImageROI(img, cvRect(0, 0, img1->width, img1->height));
cvAdd(img1, img, img, NULL);
cvSetImageROI(img, cvRect(img1->width, 0, img2->width, img2->height));
cvAdd(img2, img, img, NULL);
cvResetImageROI(img);
return img;
}
/*(自己写的函数)
将两张图像合成为一张，水平排放
参数：img1：位于左边的图像的指针，img2：位于右边的图像的指针
返回值：合成图像
*/
extern IplImage* stack_imgs_horizontal( IplImage* img1, IplImage* img2 )
{
//生成合成图像
IplImage * stacked = cvCreateImage(cvSize(img1->width+img2->width, MAX(img1->height,img2->height)),
IPL_DEPTH_8U, 3);
cvZero(stacked);//清零
cvSetImageROI(stacked, cvRect(0,0,img1->width,img1->height));
cvAdd(img1,stacked,stacked,NULL);//叠加第一张图像
cvSetImageROI(stacked, cvRect(img1->width,0,img2->width,img2->height));
cvAdd(img2,stacked,stacked,NULL);//叠加第二张图像
cvResetImageROI(stacked);
return stacked;
}
IplImage* stack_imgs(const IplImage* img1, const IplImage* img2 )
{
IplImage* stacked = cvCreateImage( cvSize( img1->width + img2->width,
MAX(img1->height, img2->height) ),
IPL_DEPTH_8U, 3 );
cvZero( stacked );
cvSetImageROI( stacked, cvRect( 0, 0, img1->width, img1->height ) );
cvAdd( img1, stacked, stacked, NULL );
cvSetImageROI( stacked, cvRect(img1->width, 0, img2->width, img2->height) );
cvAdd( img2, stacked, stacked, NULL );
cvResetImageROI( stacked );
return stacked;
}
Segment* Segment::combine(Segment *s1, Segment *s2)
{
Segment* newSegment = new Segment(*s1->seg, s1->label);
IplImage* maskAddition = cvCreateImage(cvSize(s1->seg->width, s1->seg->height), IPL_DEPTH_8U, 1);
cvAdd(s1->iplMask, s2->iplMask, maskAddition, NULL);
cvReleaseImage(&s1->iplMask);
newSegment->iplMask = maskAddition;
newSegment->mask = BwImage(newSegment->iplMask);
// weighted average colors
int s1PixelCount = s1->pixels.size();
int s2PixelCount = s2->pixels.size();
int totalPixelCount = s1PixelCount + s2PixelCount;
float s1Weight = float(s1PixelCount) / float(totalPixelCount);
float s2Weight = float(s2PixelCount) / float(totalPixelCount);
newSegment->color.r = s1->color.r * s1Weight + s2->color.r * s2Weight;
newSegment->color.g = s1->color.g * s1Weight + s2->color.g * s2Weight;
newSegment->color.b = s1->color.b * s1Weight + s2->color.b * s2Weight;
newSegment->pixels.insert(newSegment->pixels.end(), s1->pixels.begin(), s1->pixels.end());
newSegment->pixels.insert(newSegment->pixels.end(), s2->pixels.begin(), s2->pixels.end());
newSegment->updateContour();
return newSegment;
}
/* Tool function */
void motionDetection::accFrameFromVideo(CvCapture* capture){
//cvNamedWindow( "Video", CV_WINDOW_AUTOSIZE ); // Create a window to display the video
while (mCount != mFrameNumber)
{
if (cvGrabFrame(capture))
{
mFrame = cvRetrieveFrame(capture);
// convert rgb to gray
cvCvtColor(mFrame, mpFrame[mCount], CV_BGR2GRAY);
// accumulate each frame
cvAdd(mSum, mpFrame[mCount], mSum);
//cvShowImage( "Video", mpFrame[mCount] ); // display current frame
++mCount;
if (cvWaitKey(10) >= 0) {
break;
}
}
else {
break;
}
}
//cvDestroyWindow( "Video" );
}
Img GaborImage::GaborTransform(Img Image, int Frequency, int Orientation) {
orientation = Orientation;
CalculateKernel(Orientation, Frequency);
Img retImg = (IplImage*) cvClone(Image);
Img gabor_real = (IplImage*) cvClone(Image);
Img gabor_img = (IplImage*) cvClone(Image);
cvFilter2D(Image, gabor_real, KernelRealData); //image.Convolution(this.KernelRealData);
cvFilter2D(Image, gabor_img , KernelImgData); //image.Convolution(this.KernelImgData);
cvPow(gabor_real, gabor_real, 2);
cvPow(gabor_img, gabor_img, 2);
// Img gabor = (gabor_real + gabor_img).Pow(0.5);
cvAdd(gabor_real, gabor_img, retImg);
cv::Mat in = retImg;
cv::Mat out;
cv::sqrt(in, out);
IplImage dst_img = out;
cvReleaseImage(&gabor_real);
cvReleaseImage(&gabor_img);
retImg = (IplImage*) cvClone(&dst_img);
return retImg;
}
/* Standard Deviation */
IplImage* motionDetection::getStandardDeviationFrame(void) {
// Initialize
cvZero(mSum);
for (int i = 0; i < mFrameNumber; ++i) {
// frame[i] <= | frame[i] - Background Model |
cvAbsDiff(mpFrame[i], m_imgBackgroundModel, mTmp8U);
// uchar->float
cvConvert(mTmp8U, mTmp);
// mTmp = mTmp * mTmp
cvPow(mTmp, mTmp, 2.0);
// add mSum += mTmp
cvAdd(mSum, mTmp, mSum);
}
// variance: mTmp <= mSum / (mFrameNumber-1)
for (int i = 0; i < mSize.height; ++i) {
for (int j = 0; j < mSize.width; ++j) {
((float*)(mTmp->imageData + i*mTmp->widthStep))[j] = ((float*)(mSum->imageData + i*mSum->widthStep))[j] / (mFrameNumber - 1);
}
}
// standard deviation
cvPow(mTmp, mTmp, 0.5);
// float->uchar
cvConvert(mTmp, m_imgStandardDeviation);
return m_imgStandardDeviation;
}
//get the stereo pair and create the anaglyph
void createAnaglyph(IplImage *frameL, IplImage *frameR, IplImage **anaglyph){
IplImage *grayR, *grayL;
CvSize size = cvGetSize(frameL);
grayR = cvCreateImage(size, frameL->depth, 1);
grayL = cvCreateImage(size, frameL->depth, 1);
//convert images to grayscale
cvCvtColor(frameR, grayR, CV_BGR2GRAY);
cvCvtColor(frameL, grayL, CV_BGR2GRAY);
//revert to RGB (grayscale with 3 channels, all have the same pixel value)
cvCvtColor(grayR, frameR, CV_GRAY2BGR);
cvCvtColor(grayL ,frameL, CV_GRAY2BGR);
//remove channels
for(int row = 0; row < frameL->height; row++){
//set pointer to the correct position in each row
uchar* ptrR = (uchar*)(frameR->imageData + row * frameR->widthStep);
uchar* ptrL = (uchar*)(frameL->imageData + row * frameL->widthStep);
for(int col = 0; col < frameL->width; col++){
//remove blue and green channel from the right image
ptrR[3*col] = 0;
ptrR[3*col+1] = 0;
//remove red channel from the left image
ptrL[3*col+2] = 0;
}
}
//junctions images
cvAdd(frameR, frameL, *anaglyph);
}
//get the stereo pair and create the anaglyph
void createAnaglyph(IplImage *frameL, IplImage *frameR){
IplImage *anaglyph;
//remove channels
for(int row = 0; row < frameL->height; row++){
//set pointer to the correct position in each row
uchar* ptrR = (uchar*)(frameR->imageData + row * frameR->widthStep);
uchar* ptrL = (uchar*)(frameL->imageData + row * frameL->widthStep);
for(int col = 0; col < frameL->width; col++){
//remove blue and green channel from the right image
ptrR[3*col] = 0;
ptrR[3*col+1] = 0;
//remove red channel from the left image
ptrL[3*col+2] = 0;
/*//uncomment to obtain the green-magenta anaglyph
ptrR[3*col] = 0;
ptrR[3*col+2] = 0;
ptrL[3*col+1] = 0;*/
}
}
//prepare anaglyph image
CvSize size = cvGetSize(frameL);
anaglyph = cvCreateImage(size, frameL->depth, frameL->nChannels);
cvZero(anaglyph);
//junctions images
cvAdd(frameR, frameL, anaglyph);
//save junctioned image
cvSaveImage("anaglyph.bmp", anaglyph);
}
void THISCLASS::OnStep() {
// Get and check input image
IplImage *inputimage = mCore->mDataStructureImageColor.mImage;
if (! inputimage) {
AddError(wxT("No input image."));
return;
}
if (inputimage->nChannels != 3) {
AddError(wxT("The input image is not a color image."));
return;
}
// Check and update the background
if (! mFinalImage) {
mFinalImage = cvCloneImage(inputimage);
} else if (mMode == sMode_Addition) {
cvAdd(mFinalImage, inputimage, mFinalImage);
} else if (mMode == sMode_Subtraction) {
cvSub(mFinalImage, inputimage, mFinalImage);
} else if (mMode == sMode_Multiplication) {
}
// Set the display
DisplayEditor de(&mDisplayOutput);
if (de.IsActive()) {
de.SetMainImage(mFinalImage);
}
}
//--------------------------------------------------------------------------------
void ofxCvImage::operator += ( ofxCvImage& mom ) {
if( !mom.bAllocated ){
ofLogError("ofxCvImage") << "operator+=: source image not allocated";
return;
}
if( !bAllocated ){
ofLogNotice("ofxCvImage") << "operator+=: allocating to match dimensions: "
<< mom.getWidth() << " " << mom.getHeight();
allocate(mom.getWidth(), mom.getHeight());
}
if( mom.getCvImage()->nChannels == cvImage->nChannels &&
mom.getCvImage()->depth == cvImage->depth )
{
if( matchingROI(getROI(), mom.getROI()) ) {
cvAdd( cvImage, mom.getCvImage(), cvImageTemp );
swapTemp();
flagImageChanged();
} else {
ofLogError("ofxCvImage") << "operator+=: region of interest mismatch";
}
} else {
ofLogError("ofxCvImage") << "operator+=: image type mismatch";
}
}
int main() {
CvCapture* capture =0;
capture = cvCaptureFromCAM(0);
if(!capture) {
printf("Capture failure\n");
return -1;
}
IplImage* frame=0;
frame = cvQueryFrame(capture);
if(!frame) return -1;
//create a blank image and assigned to 'imgTracking' which has the same size of original video
imgTracking=cvCreateImage(cvGetSize(frame),IPL_DEPTH_8U, 3);
cvZero(imgTracking); //covert the image, 'imgTracking' to black
cvNamedWindow("Video");
cvNamedWindow("Ball");
//iterate through each frames of the video
while(true) {
frame = cvQueryFrame(capture);
if(!frame) break;
frame=cvCloneImage(frame);
cvSmooth(frame, frame, CV_GAUSSIAN,3,3); //smooth the original image using Gaussian kernel
IplImage* imgHSV = cvCreateImage(cvGetSize(frame), IPL_DEPTH_8U, 3);
cvCvtColor(frame, imgHSV, CV_BGR2HSV); //Change the color format from BGR to HSV
IplImage* imgThresh = GetThresholdedImage(imgHSV);
cvSmooth(imgThresh, imgThresh, CV_GAUSSIAN,3,3); //smooth the binary image using Gaussian kernel
//track the possition of the ball
trackObject(imgThresh);
// Add the tracking image and the frame
cvAdd(frame, imgTracking, frame);
cvShowImage("Ball", imgThresh);
cvShowImage("Video", frame);
//Clean up used images
cvReleaseImage(&imgHSV);
cvReleaseImage(&imgThresh);
cvReleaseImage(&frame);
//Wait 10mS
int c = cvWaitKey(10);
//If 'ESC' is pressed, break the loop
if((char)c==27 ) break;
}
cvDestroyAllWindows();
cvReleaseImage(&imgTracking);
cvReleaseCapture(&capture);
return 0;
}
//--------------------------------------------------------------------------------
void ofxCvFloatImage::operator += ( ofxCvFloatImage& mom ) {
if( mom.width == width && mom.height == height ) {
cvAdd( cvImage, mom.getCvImage(), cvImageTemp );
swapTemp();
} else {
cout << "error in +=, images are different sizes" << endl;
}
}
//形态学粗化不匹配运算
void lhMorpThickMiss(const IplImage* src, IplImage* dst, IplConvKernel* sefg, IplConvKernel* sebg =NULL, int type=LH_MORP_TYPE_BINARY)
{
assert(src != NULL && dst != NULL && src != dst && sefg!= NULL && sefg!=sebg);
lhMorpHMTOpen(src, dst, sefg, NULL, type);
cvAdd(src, dst, dst);
}
CvMat * LKInverseComp::computeShape(float *parameters)
{
IplImage * currentShape = cvCreateImage(cvSize(totalnumberofpoints,1),IPL_DEPTH_64F,1);
cvZero(currentShape);
IplImage * temp;
for (int m=0;m<(nS+4);m++)
{
temp = cvCloneImage(combineshapevectors[m]);
cvConvertScale(combineshapevectors[m],temp,parameters[m]);
// for (int k=0;k<combineshapevectors[m]->width;k++)
// {
// for (int d=0;d<combineshapevectors[m]->height;d++)
// {
// CvScalar s;
// s=cvGet2D(combineshapevectors[m],d,k);
// s.val[0]*=parameters[m];
// cvSet2D(temp,d,k,s);
// }
// }
cvAdd(temp,currentShape,currentShape,0);
}
cvAdd(meanShape,currentShape,currentShape,0);
static CvMat * mat = cvCreateMat(numberofpoints,2,CV_64FC1);
for (int m=0;m<numberofpoints;m++)
{
CvScalar s1 = cvGet2D(currentShape,0,2*m);
CvScalar s2 = cvGet2D(currentShape,0,2*m +1);
cvSet2D(mat,m,0,s1);
cvSet2D(mat,m,1,s2);
}
cvReleaseImage(¤tShape);
return mat;
}
void HarrisBuffer::HarrisFunction(double k, IplImage* dst)
{
// Harris function in 3D
// original space-time Harris
/*detC=
cxx.*cyy.*ctt + xx yy tt
cxy.*cyt.*cxt + 2 * xy yt xt
cxt.*cxy.*cyt - .
cxx.*cyt.*cyt - xx yt^2
cxy.*cxy.*ctt - tt xy^2
cxt.*cyy.*cxt ; yy xt^2
*/
cvMul(cxx, cyy, tmp1);
cvMul(ctt, tmp1, tmp1);
cvMul(cxy, cxt, tmp2);
cvMul(cyt, tmp2, tmp2,2);
cvAdd(tmp1,tmp2,tmp1);
cvMul(cyt,cyt,tmp2);
cvMul(cxx,tmp2,tmp2);
cvSub(tmp1,tmp2,tmp1);
cvMul(cxy,cxy,tmp2);
cvMul(ctt,tmp2,tmp2);
cvSub(tmp1,tmp2,tmp1);
cvMul(cxt,cxt,tmp2);
cvMul(cyy,tmp2,tmp2);
cvSub(tmp1,tmp2,tmp1);
//trace3C=(cxx+cyy+ctt).^3;
cvAdd(cxx,cyy,tmp2);
cvAdd(ctt,tmp2,tmp2);
cvPow(tmp2,tmp2,3);
//H=detC-stharrisbuffer.kparam*trace3C;
cvScale(tmp2,tmp2,k,0);
cvSub(tmp1,tmp2,dst);
}
//形态学对比度增强运算
void lhMorpEnhance(const IplImage* src, IplImage* dst, IplConvKernel* se=NULL, int iterations=1)
{
assert(src != NULL && dst != NULL && src != dst);
IplImage* temp = cvCloneImage(src);
lhMorpWhiteTopHat( src, temp, se, iterations );
lhMorpBlackTopHat( src, dst, se, iterations );
cvAdd(src, temp, temp);
cvSub(temp, dst, dst );
cvReleaseImage(&temp);
}
static void icvH11Ops( CvMat* X, CvMat* Y, void* userdata )
{
CvH11OpsData* h11 = (CvH11OpsData*)userdata;
h11->AOps( X, h11->AR, h11->userdata );
h11->AtOps( h11->AR, h11->AtR, h11->userdata );
double rc = h11->fe_inv_2 * cvDotProduct( h11->atr, X );
cvAddWeighted( h11->AtR, -h11->fe_inv, h11->atr, rc, 0, h11->AtR );
cvMul( h11->sigx, X, h11->tX );
cvAdd( h11->tX, h11->AtR, Y );
}
void KalmanSensorEkf::update_H(CvMat *x_pred) {
// By default we update the H by calculating Jacobian numerically
const double step = 0.000001;
cvZero(H);
for (int i=0; i<n; i++) {
CvMat H_column;
cvGetCol(H, &H_column, i);
cvZero(delta);
cvmSet(delta, i, 0, step);
cvAdd(x_pred, delta, x_plus);
cvmSet(delta, i, 0, -step);
cvAdd(x_pred, delta, x_minus);
h(x_plus, z_tmp1);
h(x_minus, z_tmp2);
cvSub(z_tmp1, z_tmp2, &H_column);
cvScale(&H_column, &H_column, 1.0/(2*step));
}
}
IplImage* GetThresholdedImage(IplImage* img)
{
IplImage* channelRed = cvCreateImage(cvGetSize(img),8,1);
IplImage* channelGreen = cvCreateImage(cvGetSize(img),8,1);
IplImage* channelBlue = cvCreateImage(cvGetSize(img),8,1);
cvSplit(img,channelBlue,channelGreen,channelRed,NULL);
cvAdd(channelBlue,channelGreen,channelGreen); //Green = Green+Blue
cvSub(channelRed,channelGreen,channelRed); //Red = Red - Green, Filtering out white area
cvThreshold(channelRed,channelRed,100,255,CV_THRESH_BINARY); //Threshold for identify Red Object
cvReleaseImage(&channelGreen);
cvReleaseImage(&channelBlue);
return channelRed;
}
static void dance_measurement(const CvMat* x_k,
const CvMat* n_k,
CvMat* z_k)
{
cvSetReal2D(z_k, 0, 0, cvGetReal2D(x_k, 0, 0));
cvSetReal2D(z_k, 1, 0, cvGetReal2D(x_k, 1, 0));
/* as above, skip this step when n_k is null */
if(n_k)
{
cvAdd(z_k, n_k, z_k);
}
}
void KalmanEkf::update_F(unsigned long tick) {
// By default we update the F by calculating Jacobian numerically
// TODO
double dt = (tick-prev_tick)/1000.0;
const double step = 0.000001;
cvZero(F);
for (int i=0; i<n; i++) {
CvMat F_column;
cvGetCol(F, &F_column, i);
cvZero(delta);
cvmSet(delta, i, 0, step);
cvAdd(x, delta, x_plus);
cvmSet(delta, i, 0, -step);
cvAdd(x, delta, x_minus);
f(x_plus, x_tmp1, dt);
f(x_minus, x_tmp2, dt);
cvSub(x_tmp1, x_tmp2, &F_column);
cvScale(&F_column, &F_column, 1.0/(2*step));
}
}
/**
* @brief CvGabor::conv_img(IplImage *src, IplImage *dst, int Type)
* @param src
* @param dst
* @param Type
*/
void CvGabor::conv_img(IplImage *src, IplImage *dst, int Type) //函数名：conv_img
{
// printf("CvGabor::conv_img 1\n");
double ve; //, re,im;
CvMat *mat = cvCreateMat(src->width, src->height, CV_32FC1);
for (int i = 0; i < src->width; i++) {
for (int j = 0; j < src->height; j++) {
ve = CV_IMAGE_ELEM(src, uchar, j, i); //CV_IMAGE_ELEM 是取图像（j，i）位置的像素值
CV_MAT_ELEM(*mat, float, i, j) = (float)ve; //转化成float 类型
}
}
// printf("CvGabor::conv_img 2\n");
CvMat *rmat = cvCreateMat(src->width, src->height, CV_32FC1);
CvMat *imat = cvCreateMat(src->width, src->height, CV_32FC1);
switch (Type)
{
case CV_GABOR_REAL:
cvFilter2D( (CvMat*)mat, (CvMat*)mat, (CvMat*)Real, cvPoint( (Width-1)/2, (Width-1)/2));
break;
case CV_GABOR_IMAG:
cvFilter2D( (CvMat*)mat, (CvMat*)mat, (CvMat*)Imag, cvPoint( (Width-1)/2, (Width-1)/2));
break;
case CV_GABOR_MAG:
cvFilter2D( (CvMat*)mat, (CvMat*)rmat, (CvMat*)Real, cvPoint( (Width-1)/2, (Width-1)/2));
cvFilter2D( (CvMat*)mat, (CvMat*)imat, (CvMat*)Imag, cvPoint( (Width-1)/2, (Width-1)/2));
cvPow(rmat,rmat,2);
cvPow(imat,imat,2);
cvAdd(imat,rmat,mat);
cvPow(mat,mat,0.5);
break;
case CV_GABOR_PHASE:
break;
}
// printf("CvGabor::conv_img 3\n");
if (dst->depth == IPL_DEPTH_8U)
{
cvNormalize((CvMat*)mat, (CvMat*)mat, 0, 255, CV_MINMAX);
for (int i = 0; i < mat->rows; i++)
{
for (int j = 0; j < mat->cols; j++)
{
ve = CV_MAT_ELEM(*mat, float, i, j);
CV_IMAGE_ELEM(dst, uchar, j, i) = (uchar)cvRound(ve);
}
}
}
CV_IMPL void cvCalS(const CvArr* srcarr,
CvArr* dstarr)
{
CV_FUNCNAME("cvCalS");
__BEGIN__;
CvMat sstub, *src;
CvMat dstub, *dst;
CvMat* src_dx=0, *src_dy=0;
CvSize size;
int i, j;
int iStep;
float* fPtr;
CV_CALL( src = cvGetMat(srcarr, &sstub ));
CV_CALL( dst = cvGetMat(dstarr, &dstub ));
if( CV_MAT_TYPE(src->type) != CV_32FC1)
CV_ERROR( CV_StsUnsupportedFormat, "Only-32bit, 1-channel input images are supported" );
if( CV_MAT_TYPE(dst->type) != CV_32FC1)
CV_ERROR( CV_StsUnsupportedFormat, "Only-32bit, 1-channel input images are supported" );
if( !CV_ARE_SIZES_EQ( src, dst ))
CV_ERROR( CV_StsUnmatchedSizes, "The input images must have the same size" );
size = cvGetMatSize( src );
src_dx = cvCreateMat(size.height, size.width, CV_32FC1 );
src_dy = cvCreateMat(size.height, size.width, CV_32FC1 );
cvSetZero(src_dx);
cvSetZero(src_dy);
iStep = dst->step / sizeof(fPtr[0]);
fPtr = dst->data.fl;
cvSobel(src, src_dx, 1, 0, 1);
cvSobel(src, src_dy, 0, 1, 1);
cvMul(src_dx, src_dx, src_dx, 0.25f*0.25f); //rescale gradient
cvMul(src_dy, src_dy, src_dy, 0.25f*0.25f); //rescale gradient
cvAdd(src_dx, src_dy, dst);
for(j=0; j<size.height; j++){
for (i=0; i<size.width; i++)
fPtr[i+iStep*j] = sqrt(fPtr[i+iStep*j])+SMALLNUM;
}
cvReleaseMat(&src_dx);
cvReleaseMat(&src_dy);
__END__;
}
void FacePredict::CalcNewTextureParams(CvMat* curParam, CvMat* newParam, int curAgeG, int newAgeG)
{
CvMat* diff = cvCreateMat(1, __nTextureModes, CV_64FC1);
CvMat* curClassicP = cvCreateMat(1, __nTextureModes, CV_64FC1);
CvMat* newClassicP = cvCreateMat(1, __nTextureModes, CV_64FC1);
cvGetRow(__TextureParamGroups, curClassicP, curAgeG);
cvGetRow(__TextureParamGroups, newClassicP, newAgeG);
cvSub(newClassicP, curClassicP, diff);
cvAdd(curParam, diff, newParam);
cvReleaseMat(&diff);
cvReleaseMat(&curClassicP);
cvReleaseMat(&newClassicP);
}
