opencv：求一幅图片的LBP纹理图（c++版本）

感觉还是使用c++版本opencv更加方便，LBP是描述的图片的局部特征，即纹理特征，有关公式和理论网上有很多我就不再重复，直接上代码。

/*
*
*/

#include "opencv2/opencv.hpp"
using namespace cv ;
using namespace std ;

Mat LBP(Mat src_image)
{
bool affiche=true;
cv::Mat Image(src_image.rows, src_image.cols, CV_8UC1);  //建立一个与src_image等高等宽的单通道图像Image
cv::Mat lbp(src_image.rows, src_image.cols, CV_8UC1);    //建立一个与src_image等高等宽的单通道图像lbp

if (src_image.channels() == 3)
cvtColor(src_image, Image, CV_BGR2GRAY);             //LBP只能处理灰度图像，这里如果传过来的是彩色照片，要转化为灰度图

unsigned center = 0;                                     //提取需要计算LBP值得中心点的灰度值
unsigned center_lbp = 0;                                 //计算center处的LBP值
//计算LBP图像
for (int row = 1; row < Image.rows-1; row++)
{
for (int col = 1; col < Image.cols-1; col++)
{
center = Image.at<uchar>(row, col);
center_lbp = 0;

if (center <= Image.at<uchar>(row - 1, col - 1))
center_lbp += 1;

if (center <= Image.at<uchar>(row - 1, col))
center_lbp += 2;

if (center <= Image.at<uchar>(row - 1, col + 1))
center_lbp += 4;

if (center <= Image.at<uchar>(row, col - 1))
center_lbp += 8;

if (center <= Image.at<uchar>(row, col + 1))
center_lbp += 16;

if (center <= Image.at<uchar>(row + 1, col - 1))
center_lbp += 32;

if (center <= Image.at<uchar>(row + 1, col))
center_lbp += 64;

if (center <= Image.at<uchar>(row + 1, col + 1))
center_lbp += 128;
lbp.at<uchar>(row, col) = center_lbp;         //把center处计算好的LBP值存放在lbp图像的相应位置
}
}
if(affiche == true)
{
cv::imshow("image LBP", lbp);
waitKey(10);
cv::imshow("grayscale",Image);
waitKey(10);
}

else
{
cv::destroyWindow("image LBP");
cv::destroyWindow("grayscale");
}

return lbp;
}
int main()
{
Mat frame1;
frame1= imread("2.jpg");
LBP(frame1);
cvWaitKey(0);
return 0;
}

实验结果：



1 原图



2 LBP图
参考内容：http://www.codeproject.com/Questions/863970/LBP-opencv-cplusplus-problem