Why can't I access the Object in my function? - c++

Question

I have a function that detects motion between two frames and stores a cropped image of only the moving Object in the variable cv::Mat result_cropped. Now I want to add a function that checks the result_cropped for black pixels. I wrote the code for that easely but I'm completly stuck on trying to implement it in my class.
For some reason my blackDetection(Mat & cropped) can't access the cropped image which results in the program crashing.
Heres my simplified code:
void ActualRec::run(){
while (isActive){
//...code to check for motion
//if there was motion a cropped image will be stored in result_cropped
number_of_changes = detectMotion(motion, result, result_cropped, region, max_deviation, color);
if(number_of_changes>=there_is_motion) {
if(number_of_sequence>0){
// there was motion detected, store cropped image - this works
saveImg(pathnameThresh, result_cropped);
if (blackDetection(result_cropped)==true){
//the cropped image has black pixels
}
else {
//the cropped image has no black pixels
}
number_of_sequence++;
}
else
{
// no motion was detected
}
}
}
bool ActualRec::blackDetection(Mat & result_cropped){
//...check for black pixels, program crashes since result_cropped is empty
//if i add imshow("test",result_cropped) I keep getting an empty window
if (blackPixelCounter>0){
return true;
}
else return false;
}
Again, the problem is that I can't manage to access result_cropped in blackDetection(Mat & result_cropped).
\\edit: my complete code for this class http://pastebin.com/3i0WdLG0 . Please someone help me. This problem doesn't make any sense for me..

Answer 1

You don't have a cv::waitKey() in blackDetection(), so you will crash before you get to the cvWaitKey() in run(). You are jumping to conclusions that result_cropped is "empty".
You have not allocated croppedBlack anywhere, so you will crash on croppedBlack.at<Vec3b>(y,x)[c] =.
Add this at the start of blackDetection() (e.g.):
croppedBlack.create(result_cropped.size(), result_cropped.type());
To make it faster see How to scan images ... with OpenCV : The efficient way
bool ActualRec::blackDetection(Mat& result_cropped)
{
croppedBlack.create(result_cropped.size(), result_cropped.type());
int blackCounter = 0;
for(int y = 0; y < result_cropped.rows; ++y)
{
Vec3b* croppedBlack_row = croppedBlack.ptr<Vec3b>(y);
Vec3b* result_cropped_row = result_cropped.ptr<Vec3b>(y);
for(int x = 0; x < result_cropped.cols; ++x)
{
for(int c = 0; c < 3; ++c)
{
croppedBlack_row[x][c] =
saturate_cast<uchar>(alpha * result_cropped_row[x][c] + beta);
}
}
}
}