opencv-计算原始LBP特征

#include <opencv2/opencv.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/nonfree/features2d.hpp>
#include <opencv2/features2d/features2d.hpp>
using namespace std;
using namespace cv;
// 计算原始LBP特征
cv::Mat OLBP(cv::Mat& srcImage)
{
const int nRows = srcImage.rows;
const int nCols = srcImage.cols;
cv::Mat resultMat(srcImage.size(), srcImage.type());
// 遍历图像，生成LBP特征
for(int y = 1; y < nRows-1; y++)
{
for(int x = 1; x < nCols-1; x++)
{
// 定义邻域
uchar neighbor[8] = {0};
neighbor[0] = srcImage.at<uchar>(y-1, x-1);
neighbor[1] = srcImage.at<uchar>(y-1, x);
neighbor[2] = srcImage.at<uchar>(y-1, x+1);
neighbor[3] = srcImage.at<uchar>(y, x+1);
neighbor[4] = srcImage.at<uchar>(y+1, x+1);
neighbor[5] = srcImage.at<uchar>(y+1, x);
neighbor[6] = srcImage.at<uchar>(y+1, x-1);
neighbor[7] = srcImage.at<uchar>(y, x-1);
// 当前图像的处理中心
uchar center = srcImage.at<uchar>(y, x);
uchar temp = 0;
// 计算LBP的值
for(int k = 0; k < 8; k++)
{
// 遍历中心点邻域
temp += (neighbor[k] >= center)* (1<<k);
}
resultMat.at<uchar>(y,x) = temp;
}
}
return resultMat;
}
int main()
{
cv::Mat srcImage = cv::imread("hand1.jpg",0);
if(!srcImage.data)
return 0;
Mat resultMat = OLBP(srcImage);
cv::imshow("srcImage", srcImage);
cv::imshow("resultMat", resultMat);
cv::waitKey(0);
return 0;
}