void MainWindow::on_Threshold_clicked()
{
this->setEnabled(false);
ThresHoldWindow threshold_window(this,_Image.getHandledData());
threshold_window.exec();
this->setEnabled(true);
}
/**
* @brief thresholds an image in a localised, adaptive way, allowing large
* illumination variations to exist in the source image and still be
* able to thresholded well
*
* @param frame the frame to threshold
* @param window_size the size of the window to use (must be odd, small is
* faster and less susceptible to illumination variations)
* @param c a constant to subtract from the threshold before it's
* applied to de-clutter the output somewhat. Good values
* are small, perhaps no greater than 10.
* @param method the method to use when thresholding a window, choose from
* { KOKI_ADAPTIVE_MEAN, KOKI_ADAPTIVE_MEDIAN }
*/
IplImage* koki_threshold_adaptive(IplImage *frame, uint16_t window_size,
int16_t c, uint8_t method)
{
IplImage *output = NULL;
koki_integral_image_t *iimg = NULL;
assert(frame != NULL && frame->nChannels == 1);
/* create the integral image to accelerate window summation */
iimg = koki_integral_image_new( frame, true );
/* create output image */
output = cvCreateImage(cvGetSize(frame),
frame->depth,
frame->nChannels);
assert(output != NULL);
if (method == 0) /* default */
method = KOKI_ADAPTIVE_MEAN;
/* threshold the image */
for (uint16_t y=0; y<frame->height; y++){
for (uint16_t x=0; x<frame->width; x++){
threshold_window(frame, iimg, output, x, y,
window_size, c, method);
}//for
}//for
koki_integral_image_free( iimg );
return output;
}
