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CV - Backprojecting a histogram.
#if !defined OFINDER
#define OFINDER
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
class ObjectFinder {
private:
float hranges[2];
const float* ranges[3];
int channels[3];
float threshold;
cv::MatND histogram;
cv::SparseMat shistogram;
bool isSparse;
public:
ObjectFinder() : threshold(0.1f), isSparse(false) {
ranges[0]= hranges; // all channels have the same range
ranges[1]= hranges;
ranges[2]= hranges;
}
// Sets the threshold on histogram values [0,1]
void setThreshold(float t) {
threshold= t;
}
// Gets the threshold
float getThreshold() {
return threshold;
}
// Sets the reference histogram
void setHistogram(const cv::MatND& h) {
isSparse= false;
histogram= h;
cv::normalize(histogram,histogram,1.0);
}
// Sets the reference histogram
void setHistogram(const cv::SparseMat& h) {
isSparse= true;
shistogram= h;
cv::normalize(shistogram,shistogram,1.0,cv::NORM_L2);
}
// Finds the pixels belonging to the histogram
cv::Mat find(const cv::Mat& image) {
cv::Mat result;
hranges[0]= 0.0; // range [0,255]
hranges[1]= 255.0;
channels[0]= 0; // the three channels
channels[1]= 1;
channels[2]= 2;
if (isSparse) { // call the right function based on histogram type
cv::calcBackProject(&image,
1, // one image
channels, // vector specifying what histogram dimensions belong to what image channels
shistogram, // the histogram we are using
result, // the resulting back projection image
ranges, // the range of values, for each dimension
255.0 // the scaling factor is chosen such that a histogram value of 1 maps to 255
);
} else {
cv::calcBackProject(&image,
1, // one image
channels, // vector specifying what histogram dimensions belong to what image channels
histogram, // the histogram we are using
result, // the resulting back projection image
ranges, // the range of values, for each dimension
255.0 // the scaling factor is chosen such that a histogram value of 1 maps to 255
);
}
// Threshold back projection to obtain a binary image
if (threshold>0.0)
cv::threshold(result, result, 255*threshold, 255, cv::THRESH_BINARY);
return result;
}
cv::Mat find(const cv::Mat& image, float minValue, float maxValue, int *channels, int dim) {
cv::Mat result;
hranges[0]= minValue;
hranges[1]= maxValue;
for (int i=0; i<dim; i++)
this->channels[i]= channels[i];
if (isSparse) { // call the right function based on histogram type
cv::calcBackProject(&image,
1, // we only use one image at a time
channels, // vector specifying what histogram dimensions belong to what image channels
shistogram, // the histogram we are using
result, // the resulting back projection image
ranges, // the range of values, for each dimension
255.0 // the scaling factor is chosen such that a histogram value of 1 maps to 255
);
} else {
cv::calcBackProject(&image,
1, // we only use one image at a time
channels, // vector specifying what histogram dimensions belong to what image channels
histogram, // the histogram we are using
result, // the resulting back projection image
ranges, // the range of values, for each dimension
255.0 // the scaling factor is chosen such that a histogram value of 1 maps to 255
);
}
// Threshold back projection to obtain a binary image
if (threshold>0.0)
cv::threshold(result, result, 255*threshold, 255, cv::THRESH_BINARY);
return result;
}
};
#endif
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