bool IPLUndistort::processInputData(IPLImage* image, int, bool)
{
// get properties
float k1 = getProcessPropertyDouble("k1");
float k2 = getProcessPropertyDouble("k2");
float k3 = getProcessPropertyDouble("k3");
float p1 = getProcessPropertyDouble("p1");
float p2 = getProcessPropertyDouble("p2");
float c1 = getProcessPropertyInt("f");
float c2 = c1;
notifyProgressEventHandler(-1);
cv::Mat cameraMatrix = (cv::Mat_<double>(3,3) << c1, 0, image->width()*0.5, 0, c2, image->height()*0.5, 0, 0, 1);
cv::Mat distCoeffs(5, 1, CV_32FC1);
distCoeffs.at<float>(0,0) = k1;
distCoeffs.at<float>(1,0) = k2;
distCoeffs.at<float>(2,0) = p1;
distCoeffs.at<float>(3,0) = p2;
distCoeffs.at<float>(4,0) = k3;
cv::Mat result;
cv::undistort(image->toCvMat(), result, cameraMatrix, distCoeffs);
delete _result;
_result = new IPLImage(result);
return true;
}
bool IPLGabor::processInputData(IPLImage* image , int, bool)
{
// delete previous result
delete _result0;
_result0 = NULL;
delete _result1;
_result1 = NULL;
delete _result2;
_result2 = NULL;
int width = image->width();
int height = image->height();
_result0 = new IPLImage( image->type(), width, height );
_result1 = new IPLImage( image->type(), width, height );
_result2 = new IPLImage( image->type(), width, height );
// get properties
int window = getProcessPropertyInt("window");
int wavelength = getProcessPropertyInt("wavelength");
double direction = getProcessPropertyDouble("direction");
double deviation = getProcessPropertyDouble("deviation");
//int progress = 0;
//int maxProgress = image->height() * image->getNumberOfPlanes();
int w2 = window/2;
int area = window*window;
double* qEven = new double [area];
double* qOdd = new double [area];
double k = 2.0 * PI / (double) wavelength;
double k2 = k * k;
double d2 = deviation * deviation;
double sig2 = 1.0 / (2.0 * d2);
double kx = k * cos( direction );
double ky = -k * sin( direction );
int index = 0;
double E = 0.0;
double O =0.0;
for( int x = -w2; x <= w2; x++ )
{
for( int y = -w2; y <= w2; y++)
{
double compensate = k2/d2;
double envelope = exp( -k2 * sig2 * (x*x+y*y) );
double DC = exp( -d2/2.0);
E += qEven[index] = compensate * envelope * ( cos( kx*x + ky*y ) - DC );
O += qOdd[index++] = compensate * envelope * ( sin( kx*x + ky*y )- DC );
}
}
for( int planeNr=0; planeNr < image->getNumberOfPlanes(); planeNr++ )
{
IPLImagePlane* plane = image->plane( planeNr );
IPLImagePlane* evenplane = _result0->plane( planeNr );
IPLImagePlane* oddplane = _result1->plane( planeNr );
IPLImagePlane* powerplane = _result2->plane( planeNr );
for(int x=w2; x<width-w2; x++)
{
for(int y=w2; y<height-w2; y++)
{
double even = 0;
double odd = 0;
double power = 0;
int i = 0;
for( int kx=-w2; kx<=w2; kx++ )
{
for( int ky=-w2; ky<=w2; ky++ )
{
double img = (double) plane->p(x+kx, y+ky);
even += img * qEven[i];
odd += img * qOdd[i++];
}
}
power = (even*even + odd*odd )*2;
even = even + 0.5;
odd = odd + 0.5;
even = (even>1.0)? 1.0 : (even<0)? 0 : even;
odd = (odd>1.0)? 1.0 : (odd<0)? 0 : odd;
power = (power>1.0)? 1.0 : (power<0)? 0 : power;
evenplane->p(x,y) = even;
oddplane->p(x,y) = odd;
powerplane->p(x,y) = power;
}
}
}
delete [] qEven;
delete [] qOdd;
return true;
}
bool IPLBinarizeSavola::processInputData(IPLImage* image , int, bool)
{
// delete previous result
delete _result;
_result = NULL;
int width = image->width();
int height = image->height();
_result = new IPLImage(image->type(), width, height);
// get properties
int window = getProcessPropertyInt("window");
double aboveMean = getProcessPropertyDouble("aboveMean");
IPLImage* mean = new IPLImage(image->type(), width, height);
IPLImage* deviation = new IPLImage(image->type(), width, height);
int progress = 0;
int maxProgress = image->height() * image->getNumberOfPlanes();
int nrOfPlanes = image->getNumberOfPlanes();
#pragma omp parallel for
for( int planeNr=0; planeNr < nrOfPlanes; planeNr++ )
{
IPLImagePlane* plane = image->plane( planeNr );
IPLImagePlane* newplane = _result->plane( planeNr );
int w2 = window/2;
float area = (float)(w2*2)*(float)(w2*2);
float minI = FLT_MAX;
float maxDeviation = 0.0;
for(int y=0; y<height; y++)
{
// progress
notifyProgressEventHandler(100*progress++/maxProgress);
for(int x=0; x<width; x++)
{
if( plane->p(x,y) < minI ) minI = plane->p(x,y);
float localMean = 0.0;
for( int kx=-w2; kx<=w2; kx++ )
{
for( int ky=-w2; ky<=w2; ky++ )
{
localMean += (float)plane->cp(x+kx,y+ky);
}
}
localMean /= area;
mean->plane(planeNr)->p(x,y) = localMean;
float dev = 0.0;
for( int kx=-w2; kx<=w2; kx++ )
{
for( int ky=-w2; ky<=w2; ky++ )
{
float diff = (float)plane->cp(x+kx, y+ky) - localMean;
dev += diff * diff;
}
}
dev = sqrt( dev / area );
deviation->plane(planeNr)->p(x,y) = dev;
if( dev > maxDeviation ) maxDeviation = dev;
}
for(int x=w2; x<width-w2; x++)
{
for(int y=w2; y<height-w2; y++)
{
float alpha = 1.0 - deviation->plane(planeNr)->p(x,y) / maxDeviation;
int T = (int) ( mean->plane(planeNr)->p(x,y) - aboveMean * alpha *( mean->plane(planeNr)->p(x,y) - minI ) );
newplane->p(x,y) = ( plane->p(x,y) >= T ) ? 0.0 : 1.0;
}
}
}
}
return true;
}
bool IPLLocalThreshold::processInputData(IPLImage* image , int, bool)
{
// delete previous result
delete _result;
_result = NULL;
int width = image->width();
int height = image->height();
if(image->type() == IPLImage::IMAGE_GRAYSCALE)
_result = new IPLImage(IPLImage::IMAGE_BW, width, height);
else
_result = new IPLImage(image->type(), width, height);
// get properties
int window = getProcessPropertyInt("window");
float aboveMean = getProcessPropertyDouble("aboveMean");
int progress = 0;
int maxProgress = image->height() * image->getNumberOfPlanes();
int nrOfPlanes = image->getNumberOfPlanes();
#pragma omp parallel for
for( int planeNr=0; planeNr < nrOfPlanes; planeNr++ )
{
IPLImagePlane* plane = image->plane( planeNr );
IPLImagePlane* newplane = _result->plane( planeNr );
int w2 = window/2;
double area = (double)window*(double)window;
for(int y=w2; y < height-w2; y++)
{
// progress
notifyProgressEventHandler(100*progress++/maxProgress);
for(int x=w2; x < width-w2; x++)
{
double localMean = 0.0;
for( int kx=-w2; kx<=w2; kx++ )
{
for( int ky=-w2; ky<=w2; ky++ )
{
localMean += (double)plane->p(x+kx,y+ky);
}
}
localMean /= area;
double deviation = 0.0;
for( int kx=-w2; kx<=w2; kx++ )
{
for( int ky=-w2; ky<=w2; ky++ )
{
double diff = (double)plane->p(x+kx, y+ky) - localMean;
deviation += diff * diff;
}
}
deviation = sqrt( deviation / area );
double T = (localMean + aboveMean*deviation);
newplane->p(x,y) = (plane->p(x,y) >= T) ? 1.0 : 0.0;
}
}
}
return true;
}
bool IPLSynthesize::processInputData(IPLImage*, int, bool)
{
if(isResultReady())
{
//return true;
}
// delete previous result
delete _result;
_result = NULL;
// get properties
_type = getProcessPropertyInt("type");
_width = getProcessPropertyInt("width");
_height = getProcessPropertyInt("height");
_amplitude = getProcessPropertyDouble("amplitude");
_offset = getProcessPropertyDouble("offset");
_wavelength = getProcessPropertyInt("wavelength");
_direction = getProcessPropertyInt("plane_direction");
_decay = getProcessPropertyInt("decay");
IPLColor color = getProcessPropertyColor("flat_color");
if( _type == 0 )
_result = new IPLImage( IPL_IMAGE_COLOR, _width, _height );
else
_result = new IPLImage( IPL_IMAGE_GRAYSCALE, _width, _height );
double dx = (double)_width / 2.0;
double dy = (double)_height / 2.0;
double direction = _direction / 180.0 * PI; // deg to rad
IPLImagePlane* plane = _result->plane( 0 );
int progress = 0;
int maxProgress = _result->height();
switch( _type )
{
case 0: // flat plane
for( int y=0; y<_height; y++ )
{
notifyProgressEventHandler(100*progress++/maxProgress);
for( int x=0; x<_width; x++ )
{
_result->plane(0)->p(x,y) = color.red();
_result->plane(1)->p(x,y) = color.green();
_result->plane(2)->p(x,y) = color.blue();
}
}
break;
case 1: // plane wave
for( int y=0; y<_height; y++ )
{
notifyProgressEventHandler(100*progress++/maxProgress);
for( int x=0; x<_width; x++ )
{
double dist = (x)*cos( direction ) + (_height-y)*sin( direction );
double fade = (_decay!=0) ? exp( -dist/_decay ) : 1.0;
double value = _amplitude * cos(dist/_wavelength * PI * 2.0) * fade + _offset;
plane->p(x,y) = ( (value<0.0)? 0.0 : (value>1.0)? 1.0 : value );
}
}
break;
case 2:// center wave
for( int y=0; y<_height; y++ )
{
notifyProgressEventHandler(100*progress++/maxProgress);
for( int x=0; x<_width; x++ )
{
double dist = sqrt( (x-dx)*(x-dx) + (y-dy)*(y-dy) );
double fade = (_decay!=0) ? exp( -dist/_decay ) : 1.0;
double value = _amplitude * cos( dist/_wavelength * PI * 2.0 ) * fade + _offset;
plane->p(x,y) = ( (value<0.0)? 0.0 : (value>1.0)? 1.0 : value );
}
}
break;
}
return true;
}
bool IPLConvolutionFilter::processInputData(IPLImage* image , int, bool useOpenCV)
{
// delete previous result
delete _result;
_result = NULL;
int width = image->width();
int height = image->height();
// get properties
_kernel = getProcessPropertyVectorInt("kernel");
_divisor = getProcessPropertyInt("divisor");
_offset = getProcessPropertyDouble("offset");
_normalize = getProcessPropertyBool("normalize");
_borders = getProcessPropertyInt("borders");
if(_normalize)
{
int sum = 0;
for(size_t i=0; i<_kernel.size(); i++)
{
sum += _kernel[i];
}
_divisor = (sum != 0 ? sum : 1);
}
if (_divisor == 0)
{
addError("Invalid divisor: 0");
return false;
}
float divFactor = 1.0f/_divisor;
int kernelWidth = (int)sqrt((float)_kernel.size());
int kernelOffset = kernelWidth / 2;
int progress = 0;
int maxProgress = image->height() * image->getNumberOfPlanes();
if (!useOpenCV)
{
_result = new IPLImage( image->type(), width, height );
#pragma omp parallel for default(shared)
for( int planeNr=0; planeNr < image->getNumberOfPlanes(); planeNr++ )
{
IPLImagePlane* plane = image->plane( planeNr );
IPLImagePlane* newplane = _result->plane( planeNr );
for(int y=0; y<plane->height(); y++)
{
// progress
notifyProgressEventHandler(100*progress++/maxProgress);
for(int x=0; x<plane->width(); x++)
{
float sum = 0;
int i = 0;
for( int ky=-kernelOffset; ky<=kernelOffset; ky++ )
{
for( int kx=-kernelOffset; kx<=kernelOffset; kx++ )
{
int h = _kernel[i++];
if( h )
{
if(_borders == 0)
{
// Crop borders
sum += plane->cp(x+kx, y+ky) * h;
}
else if(_borders == 1)
{
// Extend borders
sum += plane->bp(x+kx, y+ky) * h;
} else {
// Wrap borders
sum += plane->wp(x+kx, y+ky) * h;
}
}
}
}
sum = sum * divFactor + _offset;
sum = (sum>1.0) ? 1.0 : (sum<0) ? 0.0 : sum; // clamp to 0.0 - 1.0
newplane->p(x,y) = sum;
}
}
}
}
else
{
notifyProgressEventHandler(-1);
cv::Mat src = image->toCvMat();
cv::Mat dst;
cv::Mat kernel(kernelWidth, kernelWidth, CV_32FC1 );
int i = 0;
for( int y=0; y < kernelWidth; y++ )
for( int x=0; x < kernelWidth; x++ )
kernel.at<float>(cv::Point(x,y)) = _kernel[i++];
kernel *= divFactor;
static const int BORDER_TYPES[3] = {
cv::BORDER_CONSTANT,
cv::BORDER_REPLICATE,
cv::BORDER_WRAP
};
cv::filter2D(src, dst, -1, kernel, cv::Point(-1,-1), _offset, BORDER_TYPES[_borders]);
_result = new IPLImage(dst);
}
return true;
}
bool IPLCanny::processInputData(IPLImage* image , int, bool useOpenCV)
{
// delete previous result
delete _result;
_result = NULL;
delete _binaryImage;
_binaryImage = NULL;
int width = image->width();
int height = image->height();
_result = new IPLImage( image->type(), width, height );
_binaryImage = new IPLImage( IPLData::IMAGE_BW, width, height );
// get properties
int window = getProcessPropertyInt("window");
double sigma = getProcessPropertyDouble("sigma");
double lowThreshold = getProcessPropertyDouble("lowThreshold");
double highThreshold = getProcessPropertyDouble("highThreshold");
std::stringstream s;
s << "Window: ";
s << window;
addInformation(s.str());
//! @todo currently only the opencv implementation works
if(useOpenCV || true)
{
notifyProgressEventHandler(-1);
cv::Mat input;
cv::Mat output;
cvtColor(image->toCvMat(), input, CV_BGR2GRAY);
cv::Canny(input, output, lowThreshold*255, highThreshold*255, window);
delete _result;
_result = new IPLImage(output);
return true;
}
return false;
// Create a Gaussian 1D filter
int N = ceil( sigma * sqrt( 2.0*log( 1.0/0.015 ) ) + 1.0 );
double ssq = sigma*sigma;
double* gau = new double [window];
double* dgau = new double [window];
for( int k = -N; k <= N; ++k )
{
gau[k+N] = gauss ( (double)k, ssq );
dgau[k+N] = dGauss ( (double)k, 0, ssq );
}
// Create a directional derivative of 2D Gaussian (along X-axis)
// Since the result is symmetric along X, we can get the derivative along
// Y-axis simply by transposing the result for X direction.
// DoubleImage* dgau = new DoubleImage( window, window );
// for( int y = -N; y <= N; ++y )
// for( int x = -N; x <= N; ++x )
// dgau->f(x+N, y+N) = dGauss( x, y, ssq );
int progress = 0;
int maxProgress = width * image->getNumberOfPlanes();
int nrOfPlanes = image->getNumberOfPlanes();
//#pragma omp parallel for
for( int planeNr=0; planeNr < nrOfPlanes; planeNr++ )
{
IPLImagePlane* plane = image->plane( planeNr );
IPLImagePlane* newplane = _result->plane( planeNr );
// ******** Gaussian filtering of input image
IPLImagePlane* gI = new IPLImagePlane( width, height );
// horizontal run (normalizing original image)
IPLImagePlane* tmpI = new IPLImagePlane( width, height );
for(int x=0; x<width; x++)
{ // progress
notifyProgressEventHandler(100*progress++/maxProgress);
for(int y=0; y<height; y++)
{
double sum = 0;
int i = 0;
for( int kx=-N; kx<=N; kx++ )
{
double img = (double) plane->bp(x+kx, y);
sum += (img * gau[i++]);
}
tmpI->p(x,y) = (double) (sum);
}
}
// vertiacl run
for(int x=0; x<width; x++)
{
for(int y=0; y<height; y++)
{
double sum = 0;
int i = 0;
for( int ky=-N; ky<=N; ky++ )
{
double img = tmpI->bp(x, y+ky);
sum += (img * gau[i++]);
}
gI->p(x,y) = sum;
}
}
//delete tmpI;
// ******** Apply directional derivatives ...
// ... in x-direction
IPLImagePlane* dx = new IPLImagePlane( width, height );
for(int x=0; x<width; x++)
{
for(int y=0; y<height; y++)
{
dx->p(x,y) = 0.0;
for( int k=1; k<N; k++ )
{
dx->p(x,y) += ( gI->bp(x-k,y) - gI->bp(x+k,y) ) * dgau[k];
}
}
}
// double maxVal = 0.0;
// for(int x=0; x<width; x++)
// for(int y=0; y<height; y++)
// if( dx->f(x,y) > maxVal ) maxVal = dx->f(x,y);
// ... in y-direction
IPLImagePlane* dy = new IPLImagePlane( width, height );
for(int x=0; x<width; x++)
{
for(int y=0; y<height; y++)
{
dy->p(x,y) = 0.0;
for( int k=1; k<N; k++ )
{
dy->p(x,y) += ( gI->bp(x,y-k) - gI->bp(x,y+k) ) * dgau[k];
}
}
}
// ******** Compute magnitude and binarization thresholds
IPLImagePlane* mag = new IPLImagePlane( width, height );
double magMax = 0.0;
double magMin = 999999999.0;
for(int x=0; x<width; x++)
{
for(int y=0; y<height; y++)
{
double val = sqrt( dx->p(x,y)*dx->p(x,y) + dy->p(x,y)*dy->p(x,y) );
mag->p(x,y) = val;
if( val > magMax ) magMax = val;
if( val < magMin ) magMin = val;
}
}
//// ******** Non-maxima suppression - edge pixels should be a local maximum
_orientedImage = new IPLOrientedImage( width, height );
for(int x=0; x<width; x++)
{
for(int y=0; y<height; y++)
{
double ix = dx->p(x,y);
double iy = dy->p(x,y);
double g = mag->p(x,y);
// determine 4-neighbor direction of gradient
int dir4 = 0;
if( (iy<=0.0 && ix>-iy) || (iy>=0.0 && ix<-iy) )
dir4 = 1;
else if( (ix>0.0 && -iy>=ix) || (ix<0.0 && -iy<=ix) )
dir4 = 2;
else if( (ix<=0.0 && ix>iy) || (ix>=0.0 && ix<iy) )
dir4 = 3;
else if( (iy<0.0 && ix<=iy) || (iy>0.0 && ix>=iy) )
dir4 = 4;
else
continue;
double gradmag1, gradmag2, d;
switch(dir4)
{
case 1: d = std::fabs(iy/ix);
gradmag1 = mag->bp(x+1,y)*(1-d) + mag->bp(x+1,y-1)*d;
gradmag2 = mag->bp(x-1,y)*(1-d) + mag->bp(x-1,y+1)*d;
break;
case 2: d = std::fabs(ix/iy);
gradmag1 = mag->bp(x,y-1)*(1-d) + mag->bp(x+1,y-1)*d;
gradmag2 = mag->bp(x,y+1)*(1-d) + mag->bp(x-1,y+1)*d;
break;
case 3: d = std::fabs(ix/iy);
gradmag1 = mag->bp(x,y-1)*(1-d) + mag->bp(x-1,y-1)*d;
gradmag2 = mag->bp(x,y+1)*(1-d) + mag->bp(x+1,y+1)*d;
break;
case 4: d = std::fabs(iy/ix);
gradmag1 = mag->bp(x-1,y)*(1-d) + mag->bp(x-1,y-1)*d;
gradmag2 = mag->bp(x+1,y)*(1-d) + mag->bp(x+1,y+1)*d;
break;
}
if( g > gradmag1 && g > gradmag2 )
{
_orientedImage->magnitude(x,y) = g;
_orientedImage->phase(x,y) = atan2(iy,ix);
}
}
}
for(int x=0; x<width; x++)
{
for(int y=0; y<height; y++)
{
_orientedImage->magnitude(x,y) /= magMax;
double val = _orientedImage->magnitude(x,y)*255.0;
// double val = mag->f(x,y)/magMax*255.0;
if (val > 255.0 ) val = 255.0;
if (val < 0.0 ) val = 0.0;
newplane->p(x,y) = (unsigned char ) val;
}
}
// ******** Binarize with hysteresis threshold
double hist[ 256 ];
for( int i=0; i<256; ++i )
hist[i] = 0;
int pixCount = 0;
for(int x=0; x<width; x++)
{
for(int y=0; y<height; y++)
{
if( _orientedImage->magnitude(x,y) > 0.0 )
{
int index = floor( _orientedImage->magnitude(x,y)*256.0+0.5 );
++hist[ index ];
++pixCount;
}
}
}
double PercentOfPixelsNotEdges = 0.7*pixCount;
double highThresh = 0.0;
double cumsum = 0.0;
for( int i=0; i<256; ++i )
{
cumsum += hist[i];
if( cumsum > PercentOfPixelsNotEdges )
{
highThresh = (double)i / 256.0;
break;
}
}
double lowThresh = 0.4 * highThresh;
IPLImagePlane* binPlane = _binaryImage->plane( 0 );
for(int x=0; x<width; x++)
{
for(int y=0; y<height; y++)
{
if(_orientedImage->magnitude(x,y) >= highThresh)
trace(x, y, lowThresh, _orientedImage, binPlane);
}
}
//delete dx;
//delete dy;
//delete gI;
thinning(_orientedImage, binPlane, newplane );
}
//delete [] gau;
//delete [] dgau;
return true;
}
