opencv中与split()与merge()的问题

错误：opencv文档中的core，“与opencv1同时使用“的例程，运行时报内存访问冲突的错误。 如图：

原因是由于vector<Mat>planes;容器planes为空，与I_YUV不符合，可以改为Mat planes[3]。

改后marge需要输入三个参数，输入矩阵，输入矩阵个数，输出矩阵

即：把merge(planes, I_YUV);改为merge(planes,3, I_YUV);

修改之后的代码：

#include<opencv2/opencv.hpp>
#include<stdlib.h>
#include<iostream>

using namespace std;
using namespace cv;

static void help(char* progName)
{
cout << endl << progName
<< " shows how to use cv::Mat and IplImages together (converting back and forth)." << endl
<< "Also contains example for image read, spliting the planes, merging back and " << endl
<< " color conversion, plus iterating through pixels. " << endl
<< "Usage:" << endl
<< progName << " [image-name Default: ../data/lena.jpg]" << endl << endl;
}

//! [start]
// comment out the define to use only the latest C++ API
#define DEMO_MIXED_API_USE

#ifdef DEMO_MIXED_API_USE
#  include <opencv2/highgui/highgui_c.h>
#  include <opencv2/imgcodecs/imgcodecs_c.h>
#endif

int main(int argc, char** argv)
{
help(argv[0]);
const char* imagename =  "DSC_2257.JPG";

#ifdef DEMO_MIXED_API_USE
Ptr<IplImage> IplI(cvLoadImage(imagename));      // Ptr<T> is a safe ref-counting pointer class
if (!IplI)
{
cerr << "Can not load image " << imagename << endl;
return -1;
}
Mat I = cv::cvarrToMat(IplI); // Convert to the new style container. Only header created. Image not copied.
#else
Mat I = imread(imagename);        // the newer cvLoadImage alternative, MATLAB-style function
if (I.empty())                   // same as if( !I.data )
{
cerr << "Can not load image " << imagename << endl;
return -1;
}
#endif
//! [start]

//! [new]
// convert image to YUV color space. The output image will be created automatically.
Mat I_YUV;
cvtColor(I, I_YUV, COLOR_BGR2YCrCb);

Mat planes[3];    // Use the STL's vector structure to store multiple Mat objects
split(I_YUV, planes);  // split the image into separate color planes (Y U V)
//! [new]

#if 1 // change it to 0 if you want to see a blurred and noisy version of this processing
//! [scanning]
// Mat scanning
// Method 1. process Y plane using an iterator
MatIterator_<uchar> it = planes[0].begin<uchar>(), it_end = planes[0].end<uchar>();
for (; it != it_end; ++it)
{
double v = *it * 1.7 + rand() % 21 - 10;
*it = saturate_cast<uchar>(v*v / 255);
}

for (int y = 0; y < I_YUV.rows; y++)
{
// Method 2. process the first chroma plane using pre-stored row pointer.
uchar* Uptr = planes[1].ptr<uchar>(y);
for (int x = 0; x < I_YUV.cols; x++)
{
Uptr[x] = saturate_cast<uchar>((Uptr[x] - 128) / 2 + 128);

// Method 3. process the second chroma plane using individual element access
uchar& Vxy = planes[2].at<uchar>(y, x);
Vxy = saturate_cast<uchar>((Vxy - 128) / 2 + 128);
}
}
//! [scanning]

#else

//! [noisy]
Mat noisyI(I.size(), CV_8U);           // Create a matrix of the specified size and type

// Fills the matrix with normally distributed random values (around number with deviation off).
// There is also randu() for uniformly distributed random number generation
randn(noisyI, Scalar::all(128), Scalar::all(20));

// blur the noisyI a bit, kernel size is 3x3 and both sigma's are set to 0.5
GaussianBlur(noisyI, noisyI, Size(3, 3), 0.5, 0.5);

const double brightness_gain = 0;
const double contrast_gain = 1.7;

#ifdef DEMO_MIXED_API_USE
// To pass the new matrices to the functions that only work with IplImage or CvMat do:
// step 1) Convert the headers (tip: data will not be copied).
// step 2) call the function   (tip: to pass a pointer do not forget unary "&" to form pointers)

IplImage cv_planes_0 = planes[0], cv_noise = noisyI;
cvAddWeighted(&cv_planes_0, contrast_gain, &cv_noise, 1, -128 + brightness_gain, &cv_planes_0);
#else
addWeighted(planes[0], contrast_gain, noisyI, 1, -128 + brightness_gain, planes[0]);
#endif

const double color_scale = 0.5;
// Mat::convertTo() replaces cvConvertScale.
// One must explicitly specify the output matrix type (we keep it intact - planes[1].type())
planes[1].convertTo(planes[1], planes[1].type(), color_scale, 128 * (1 - color_scale));

// alternative form of cv::convertScale if we know the datatype at compile time ("uchar" here).
// This expression will not create any temporary arrays ( so should be almost as fast as above)
planes[2] = Mat_<uchar>(planes[2] * color_scale + 128 * (1 - color_scale));

// Mat::mul replaces cvMul(). Again, no temporary arrays are created in case of simple expressions.
planes[0] = planes[0].mul(planes[0], 1. / 255);
//! [noisy]
#endif

//! [end]
merge(planes,3, I_YUV);                // now merge the results back
cvtColor(I_YUV, I, COLOR_YCrCb2BGR);  // and produce the output RGB image

namedWindow("image with grain", WINDOW_AUTOSIZE);   // use this to create images

#ifdef DEMO_MIXED_API_USE
// this is to demonstrate that I and IplI really share the data - the result of the above
// processing is stored in I and thus in IplI too.
cvShowImage("image with grain", IplI);
#else
imshow("image with grain", I); // the new MATLAB style function show
#endif
//! [end]
waitKey();

// Tip: No memory freeing is required!
//      All the memory will be automatically released by the Vector<>, Mat and Ptr<> destructor.
return 0;
}