opencv 3.0.0 测试lbp效果

opencv 3.0.0 测试lbp效果

参考资料：
http://www.bytefish.de/blog/local_binary_patterns/

lbp从原理上来说，是相对比较好理解的，但是后面怎么使用，还没有弄明白，先直观的感受一下图像的lbp纹理特征的视觉效果。

代码：

/*
 * lbptest.cpp
 *
 *  Created on: Dec 29, 2015
 *      Author: gumh
 */


#include <opencv2/opencv.hpp>
#include <limits>
using namespace std;
using namespace cv;

//原始的LBP算法
//使用模板参数
/**
*将原图去除最外围的一圈，里面的每个都作为中心点，来计算这个中心点相应矩形区域
*的lbp特征值。
*算出来的这个lbp特征值，就是目标mat的值，
*目标mat的大小是原始mat的（rows-2,cols-2)
*/
template <typename _Tp>
void OLBP_(const Mat& src, Mat& dst) {
    dst = Mat::zeros(src.rows-2, src.cols-2, CV_8UC1);
    for(int i=1;i<src.rows-1;i++) {
        for(int j=1;j<src.cols-1;j++) {
            _Tp center = src.at<_Tp>(i,j);
            unsigned char code = 0;
            code |= (src.at<_Tp>(i-1,j-1) > center) << 7;
            code |= (src.at<_Tp>(i-1,j) > center) << 6;
            code |= (src.at<_Tp>(i-1,j+1) > center) << 5;
            code |= (src.at<_Tp>(i,j+1) > center) << 4;
            code |= (src.at<_Tp>(i+1,j+1) > center) << 3;
            code |= (src.at<_Tp>(i+1,j) > center) << 2;
            code |= (src.at<_Tp>(i+1,j-1) > center) << 1;
            code |= (src.at<_Tp>(i,j-1) > center) << 0;
            dst.at<unsigned char>(i-1,j-1) = code;
            if(i==1)
            cout<<"("<<i-1<<","<<j-1<<")="<<(unsigned)code<<" ";
        }
        if(i==1)
        cout<<endl;
    }
}

template <typename _Tp>
void ELBP_(const Mat& src, Mat& dst, int radius, int neighbors) {
    neighbors = max(min(neighbors,31),1); // set bounds...
    // Note: alternatively you can switch to the new OpenCV Mat_
    // type system to define an unsigned int matrix... I am probably
    // mistaken here, but I didn't see an unsigned int representation
    // in OpenCV's classic typesystem...
    dst = Mat::zeros(src.rows-2*radius, src.cols-2*radius, CV_32SC1);
    for(int n=0; n<neighbors; n++) {
        // sample points
        float x = static_cast<float>(radius) * cos(2.0*M_PI*n/static_cast<float>(neighbors));
        float y = static_cast<float>(radius) * -sin(2.0*M_PI*n/static_cast<float>(neighbors));
        // relative indices
        int fx = static_cast<int>(floor(x));
        int fy = static_cast<int>(floor(y));
        int cx = static_cast<int>(ceil(x));
        int cy = static_cast<int>(ceil(y));
        // fractional part
        float ty = y - fy;
        float tx = x - fx;
        // set interpolation weights
        float w1 = (1 - tx) * (1 - ty);
        float w2 =      tx  * (1 - ty);
        float w3 = (1 - tx) *      ty;
        float w4 =      tx  *      ty;
        // iterate through your data
        for(int i=radius; i < src.rows-radius;i++) {
            for(int j=radius;j < src.cols-radius;j++) {
                float t = w1*src.at<_Tp>(i+fy,j+fx) + w2*src.at<_Tp>(i+fy,j+cx) + w3*src.at<_Tp>(i+cy,j+fx) + w4*src.at<_Tp>(i+cy,j+cx);
                // we are dealing with floating point precision, so add some little tolerance
                dst.at<unsigned int>(i-radius,j-radius) += ((t > src.at<_Tp>(i,j)) && (abs(t-src.at<_Tp>(i,j)) > std::numeric_limits<float>::epsilon())) << n;
            }
        }
    }
}

int main(int argc, char* argv[]) {

    Mat color_face = imread("../../lena.jpg",CV_LOAD_IMAGE_ANYDEPTH | CV_LOAD_IMAGE_ANYCOLOR);
    if(color_face.empty()){
        cout<<"read picture fail!\n";
        return -1;
    }

    Mat olbp_face = Mat::zeros(color_face.size(),color_face.type()) ;

    //change to grey color picture
    cvtColor(color_face, olbp_face, CV_BGR2GRAY);

    //显示原始的输入图像
    cvNamedWindow("Src Image",CV_WINDOW_AUTOSIZE);
    imshow("Src Image",olbp_face);

    //计算输入图像的LBP纹理特征
    Mat lbp_face;//= Mat::zeros(color_face.size(),color_face.type()) ;
    OLBP_<uchar>(olbp_face,lbp_face);

    //显示LBP纹理特征图
    namedWindow("LBP Image1",1);
    imshow("LBP Image1",lbp_face);


    //use elbp
//  Mat elbp_face;
//  ELBP_<uchar>(olbp_face,elbp_face,2,4);


    waitKey();

    return 0;
}

CMakeLists.txt

cmake_minimum_required(VERSION 2.8)
project( lbptest )
set(OpenCV_DIR /home/zzz/software/opencv-3.0.0/release)
include_directories(/home/zzz/software/opencv-3.0.0/build/include)
find_package( OpenCV REQUIRED )
add_executable( lbptest lbptest.cpp )
target_link_libraries( lbptest ${OpenCV_LIBS} )

效果：
灰度图：

转换为lbp特征图：