/*
* compute the second order.
*/
bool harrisCorners::getSecondOrder(channel& gx,
channel& gy,
channel& fxy) const {
const parameters& par = getParameters();
fxy.resize(gx.size(),false,false);
gaussKernel2D<float> gk(par.kernelSize,par.variance);
convolution filter;
convolution::parameters filterPar;
filterPar.boundaryType = lti::Constant;
filterPar.setKernel(gk);
filter.setParameters(filterPar);
channel::iterator igx=gx.begin();
channel::iterator igxend=gx.end();
channel::iterator igy=gy.begin();
channel::iterator ifxy=fxy.begin();
float tx, ty;
while (igx!=igxend) {
tx=(*igx);
ty=(*igy);
(*igx)=tx*tx;
(*igy)=ty*ty;
(*ifxy)=tx*ty;
++igx; ++igy; ++ifxy;
}
return (filter.apply(gx) && filter.apply(gy) && filter.apply(fxy));
}
// split image into float channels
bool splitImageToxyY::apply(const image& img,
channel& c1,
channel& c2,
channel& c3) const {
point p; // coordinates
rgbPixel pix; // single Pixel Element in RGB-values...
float Y; // channels
float X, XYZ; // help variables
// make the channels size of source image...
c1.resize(img.rows(),img.columns(),0,false,false);
c2.resize(img.rows(),img.columns(),0,false,false);
c3.resize(img.rows(),img.columns(),0,false,false);
for (p.y=0;p.y<img.rows();p.y++)
for (p.x=0;p.x<img.columns();p.x++) {
// take pixel at position p
pix = img.at(p);
// see Gonzales & Woods for explanation of magic numbers
X = (((float)(pix.getRed())) *0.412453f +
((float)(pix.getGreen())) *0.357580f +
((float)(pix.getBlue())) *0.180423f)/255.0f; // x
Y = (((float)(pix.getRed())) *0.212671f +
((float)(pix.getGreen())) *0.715160f +
((float)(pix.getBlue())) *0.072169f)/255.0f; // y
XYZ = (((float)(pix.getRed())) *0.644458f +
((float)(pix.getGreen())) *1.191933f +
((float)(pix.getBlue())) *1.202819f)/255.0f; // Y
if (XYZ>0.0f) {
c1.at(p) = X/XYZ; // x
c2.at(p) = Y/XYZ; // y
}
else {
c1.at(p) = 0; // x
c2.at(p) = 0; // y
}
c3.at(p) = Y; // Y
} // loop
return true;
}
/*
* compute cornerness
*/
bool harrisCorners::getCornerness(const channel& fxx,
const channel& fxy,
const channel& fyy,
const float scale,
channel& cornerness,
float& maxCornerness) const {
// we can assume that all channels are connected, but try it out if not
if ((fxx.getMode() != channel::Connected) ||
(fxy.getMode() != channel::Connected) ||
(fyy.getMode() != channel::Connected)) {
setStatusString("Channels not contigous in getCornerness");
return false;
}
if (fxx.empty() || fxy.empty() || fyy.empty()) {
cornerness.clear();
maxCornerness = 0.0f;
return false;
}
int i;
const int end = fxx.rows()*fxx.columns();
const float *const pfxx = &fxx.at(0);
const float *const pfxy = &fxy.at(0);
const float *const pfyy = &fyy.at(0);
cornerness.resize(fxx.size(),0,false,false);
float* pcor = &cornerness.at(0);
float det,trace,txx,txy,tyy,c;
float maxc = 0.0f;
for (i=0;i<end;++i) {
txx=pfxx[i];
txy=pfxy[i];
tyy=pfyy[i];
det=txx*tyy - txy*txy;
trace=txx+tyy;
c = det-scale*trace*trace;
pcor[i]=c;
if (c>maxc) {
maxc=c;
}
}
maxCornerness = maxc;
return true;
}
bool hessianFunctor::classicXY(const channel& src, channel& xy) const {
if (src.columns() < 3) {
setStatusString("width less than 3");
xy.clear();
return false;
}
if (src.rows() < 3) {
setStatusString("height less than 3");
xy.clear();
return false;
}
if (src.getMode()!=channel::Connected) {
setStatusString("src must be Connected");
xy.clear();
return false;
}
const int width = src.columns();
const int height = src.rows();
xy.resize(height,width,0.f,false,false);
float* fpxy = &xy.at(0,0);
const float* fpSrc = &src.at(0,0);
const float* rowy;
const float* colx;
float* pidxy;
const int w1 = width-1;
const int w2 = width-2;
const int last = (height-1)*width; // index of begin of last row
const int lastRow = -w1; // offset from actual column pointer to
// last row
const int nextRow = width+1; // offset from actual column pointer to
// next row
const int nextRow2 = width+2; // offset from actual column pointer to
// next row + 1
// top-left corner
fpxy[0]=(fpSrc[0]-fpSrc[1]-fpSrc[width]+fpSrc[nextRow]);
// top
pidxy = &fpxy[1];
for (colx=&fpSrc[0],rowy=&fpSrc[w1];
colx<rowy;
++colx,++pidxy) {
*pidxy=(*colx - colx[2] - colx[width] + colx[nextRow2]);
}
// top-right corner
fpxy[w1]=(fpSrc[w2]-fpSrc[w1]-fpSrc[w2+width]+fpSrc[w1+width]);
// main loop (begin at coordinates (1,0)
pidxy = &fpxy[width];
const float *const rowEnd = &fpSrc[last];
for (rowy=&fpSrc[width];
rowy<rowEnd;
rowy+=width) {
// left side
*pidxy=(rowy[-width] - rowy[lastRow] - rowy[width] + rowy[nextRow]);
++pidxy;
// middle
const float *const colEnd = &rowy[w2];
for (colx=rowy;
colx<colEnd;
++colx,++pidxy) {
*pidxy=(colx[-width] - colx[-w2] - colx[width] + colx[nextRow2]);
}
// right side
*pidxy=(colx[-width] - colx[lastRow] - colx[width] + colx[nextRow]);
++pidxy;
}
// bottom-left corner
fpxy[last]=(fpSrc[last+1]-fpSrc[last]);
// bottom
pidxy = &fpxy[last+1];
const float *const colEnd = &rowEnd[w2];
for (colx=rowEnd;
colx<colEnd;
++colx,++pidxy) {
*pidxy=(colx[-width] - colx[-w2] - *colx + colx[2]);
}
// bottom-right corner
fpxy[last+w1]=(fpSrc[last-2]-fpSrc[last-1]-fpSrc[last+w2]+fpSrc[last+w1]);
return true;
};
// return probability channel
bool probabilityMap2D::apply(const channel8& src1, const channel8& src2, channel& dest) const {
const parameters& param = getParameters();
point chnl1_size = src1.size();
point chnl2_size = src2.size();
// size of src1 equals src2 ?
if ( (chnl1_size.x != chnl2_size.x) || (chnl1_size.y != chnl2_size.y) ) {
setStatusString("probabilityMap2D: channels do not match");
return false;
}
// the color model MUST have 2 dimensions!
if (probabilityHistogram.dimensions() == 2) {
// resize probability channel
dest.resize(src1.size());
ivector theBin(2);
// compute first iteration
int y;
vector<channel8::value_type>::const_iterator srcIterator1, eit1;
vector<channel8::value_type>::const_iterator srcIterator2, eit2;
vector<channel::value_type>::iterator destIterator;
for (y=0;y<src1.rows();++y) {
srcIterator1 = src1.getRow(y).begin();
eit1 = src1.getRow(y).end();
srcIterator2 = src2.getRow(y).begin();
eit2 = src2.getRow(y).end();
destIterator = dest.getRow(y).begin();
while (srcIterator1 != eit1) {
theBin[0] = lookupTable[0][*srcIterator1];
theBin[1] = lookupTable[1][*srcIterator2];
(*destIterator)=static_cast<float>(probabilityHistogram.at(theBin));
srcIterator1++;
srcIterator2++;
destIterator++;
}
}
// compute all other iterations
if (param.iterations > 1) {
int i;
if (param.gaussian) {
gaussKernel2D<float> gk(param.windowSize,param.variance);
convolution convolver;
convolution::parameters convParam;
convParam.boundaryType = lti::Mirror;
convParam.setKernel(gk);
convolver.setParameters(convParam);
for (i=1;i<param.iterations;++i) {
convolver.apply(dest);
computeMap(src1,src2,dest);
}
} else {
squareConvolution<float> convolver;
squareConvolution<float>::parameters convParam;
convParam.boundaryType = lti::Mirror;
convParam.initSquare(param.windowSize);
convolver.setParameters(convParam);
for (i=1;i<param.iterations;++i) {
convolver.apply(dest);
computeMap(src1,src2,dest);
}
}
} // of (param.iterations > 1)
return true;
} // of (probabilityHistogram.dimensions() == 2)
setStatusString("probabilityMap2D: no models loaded");
return false;
}
