Examples: MeanThreshold

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Content of the heuristics/examples/meanThreshold.cpp file:

/** @file   meanThreshold.cpp
    @author Philip Abbet (philip.abbet@idiap.ch)
 
    Example of a heuristic: MeanThreshold. The features indicates if the
    corresponding (grayscale) pixels is above or below the mean value of the
    processed region of interest.
*/
 
#include <mash/heuristic.h>
 
using namespace Mash;
 
 
//------------------------------------------------------------------------------
/// @brief  The 'MeanThreshold' heuristic class
//------------------------------------------------------------------------------
class MeanThresholdHeuristic: public Heuristic
{
    //_____ Construction / Destruction __________
public:
    MeanThresholdHeuristic();
    virtual ~MeanThresholdHeuristic();
 
 
    //_____ Implementation of Heuristic __________
public:
    virtual unsigned int dim();
 
    virtual void prepareForCoordinates();
 
    virtual scalar_t computeFeature(unsigned int feature_index);
 
 
    //_____ Attributes __________
protected:
    float _mean;
};
 
 
//------------------------------------------------------------------------------
/// @brief  Creation function of the heuristic
//------------------------------------------------------------------------------
extern "C" Heuristic* new_heuristic()
{
    return new MeanThresholdHeuristic();
}
 
 
 
/************************* CONSTRUCTION / DESTRUCTION *************************/
 
MeanThresholdHeuristic::MeanThresholdHeuristic()
: _mean(0.0f)
{
}
 
 
MeanThresholdHeuristic::~MeanThresholdHeuristic()
{
}
 
 
/************************* IMPLEMENTATION OF Heuristic ************************/
 
unsigned int MeanThresholdHeuristic::dim()
{
    // We have has many features than pixels in the region of interest
    unsigned int roi_size = roi_extent * 2 + 1;
    return roi_size * roi_size;
}
 
 
void MeanThresholdHeuristic::prepareForCoordinates()
{
    // Compute the coordinates of the top-left pixel of the region of interest
    unsigned int x0 = coordinates.x - roi_extent;
    unsigned int y0 = coordinates.y - roi_extent;
 
    // Compute the mean value of the region of interest
    byte_t** pLines = image->grayLines();
 
    _mean = 0.0f;
    for (unsigned int y = 0; y < roi_extent * 2 + 1; ++y)
    {
        for (unsigned int x = 0; x < roi_extent * 2 + 1; ++x)
            _mean += pLines[y0 + y][x0 + x];
    }
 
    _mean /= dim();
}
 
 
scalar_t MeanThresholdHeuristic::computeFeature(unsigned int feature_index)
{
    // Compute the coordinates of the top-left pixel of the region of interest
    unsigned int x0 = coordinates.x - roi_extent;
    unsigned int y0 = coordinates.y - roi_extent;
 
    // Compute the coordinates of the pixel corresponding to the feature, in
    // the region of interest
    unsigned int roi_size = roi_extent * 2 + 1;
    unsigned int x = feature_index % roi_size;
    unsigned int y = (feature_index - x) / roi_size;
 
    // Compute the feature value
    byte_t** pLines = image->grayLines();
    if (pLines[y0 + y][x0 + x] >= _mean)
        return 1.0f;
 
    return 0.0f;
}