Compiler error while Normalizing Histogram - opencv

Question

I am using the following code to normalize the histogram of a sequence of frames from video file and change the frame only if difference returned by compareHist method is over a certain threshold:
bool
DMSUSBVideoDevicePlugin::_hasImageChanged()
{
using namespace cv;
Mat src = cv::Mat(_captureHeight, _captureWidth, CV_8UC3, (void*) _imageData);
/// Separate the image in 3 places ( B, G and R )
vector<Mat> bgr_planes;
split( src, bgr_planes );
/// Establish the number of bins
int histSize = 256;
/// Set the ranges ( for B,G,R) )
float range[] = { 0, 256 } ;
const float* histRange = { range };
bool uniform = true;
bool accumulate = false;
SparseMat b_hist, g_hist, r_hist;
/// Compute the histograms:
calcHist( &bgr_planes[1], 1, 0, Mat(), g_hist, 1, &histSize, &histRange, uniform, accumulate);
// Draw the histograms for B, G and R
int hist_w = 512; int hist_h = 400;
int bin_w = cvRound( (double) hist_w/histSize );
Mat histImage( hist_h, hist_w, CV_8UC3, Scalar( 0,0,0) );
normalize(g_hist, g_hist, 0.0, histImage.rows, 32, -1, SparseMat());
static bool isFirstFrame = true;
if(isFirstFrame)
{
_lastGreenHistogram = g_hist;
isFirstFrame = false;
return true;
}
double diff = compareHist(g_hist, _lastGreenHistogram, CV_COMP_BHATTACHARYYA );
_lastGreenHistogram = g_hist;
std::cout << "Diff val: " << diff << std::endl;
if(diff > 1.f)
{
return true;
}
return false;
}
However, I get a compiler error saying:
1>.\DMSUSBVideoDevicePlugin.cpp(454) : error C2665: 'cv::normalize' :
none of the 2 overloads could convert all the argument types 1>
C:\opencv\build\include\opencv2/core/core.hpp(2023): could be 'void
cv::normalize(cv::InputArray,cv::OutputArray,double,double,int,int,cv::InputArray)'
What am I doing wrong?

Answer 1

You're trying to convert an SparseMat to an InputArray. This isn't legal. InputArray expects a container with sequential memory.
From the docs:
where InputArray is a class that can be constructed from Mat,
Mat, Matx, std::vector, std::vector >
or std::vector. It can also be constructed from a matrix
expression.
You can read on InputArray here.
You should use a regular cv::Mat object as the normalize function will not create a copy of the source.
Same goes for OutputArray.