灰度共生矩阵及相关特征值的计算——opencv
#include(6, 6) << 0, 1, 2, 3, 0, 1, 1, 2, 3, 0, 1, 2, 2, 3, 0, 1, 2, 3, 3, 0, 1, 2, 3, 0, 0, 1, 2, 3, 0, 1, 1, 2, 3, 0, 1, 2 );
//src = (Mat_(4, 4) << 1, 17, 0, 3,3,2,20,5,26,50,1,2,81,9,25,1);
getglcm_horison(src_gray, dst_horison);
getglcm_vertical(src_gray, dst_vertical);
getglcm_45(src_gray, dst_45);
getglcm_135(src_gray, dst_135);
double eng_horison=0, con_horison=0, idm_horison=0, asm_horison=0;
feature_computer(dst_horison, asm_horison, eng_horison, con_horison, idm_horison);
cout << "asm_horison:" << asm_horison << endl;
cout << "eng_horison:" << eng_horison << endl;
cout << "con_horison:" << con_horison << endl;
cout << "idm_horison:" << idm_horison << endl;
/* for (int i = 0; i < dst_horison.rows; i++)
{
int *data = dst_horison.ptr(i);
for (int j = 0; j < dst_horison.cols; j++)
{
cout << data[j] << " ";
}
cout << endl;
}
cout << endl;
for (int i = 0; i < dst_vertical.rows; i++)
{
int *data = dst_vertical.ptr(i);
for (int j = 0; j < dst_vertical.cols; j++)
{
cout << data[j] << " ";
}
cout << endl;
}
cout << endl;
for (int i = 0; i < dst_45.rows; i++)
{
int *data = dst_45.ptr(i);
for (int j = 0; j < dst_45.cols; j++)
{
cout << data[j] << " ";
}
cout << endl;
}
cout << endl;
for (int i = 0; i < dst_135.rows; i++)
{
int *data = dst_135.ptr(i);
for (int j = 0; j < dst_135.cols; j++)
{
cout << data[j] << " ";
}
cout << endl;
}*/
system("pause");
return 0;
}参考：
灰度共生矩阵的定义与理解：http://www.cnblogs.com/xiangshancuizhu/archive/2011/07/24/2115266.html
opencv实现：
http://blog.csdn.net/cxf7394373/article/details/6988229
http://download.csdn.net/download/sxnzxz/3419181