复杂背景下的文本检测

Question

我有以下代码来计算Daubechie 4小波变换图像（LL，LH，HL，HH子带）和能量特征。在this论文中是一篇关于如何从复杂背景中检测文本的教程，但我不知道如何继续这样做。有人可以帮助我，也许可以解释我如何计算图像的小波能量直方图，或者如何实现纸上的内容？

#include <opencv2/highgui.hpp>
#include <opencv2/core.hpp>
#include <opencv2/imgproc.hpp>
#include <iostream>
#include <math.h>


#define h0 (1+sqrt(3))/(4*sqrt(2))
#define h1 (3+sqrt(3))/(4*sqrt(2))
#define h2 (3-sqrt(3))/(4*sqrt(2))
#define h3 (1-sqrt(3))/(4*sqrt(2))

#define g0 h3
#define g1 -h2
#define g2 h1
#define g3 -h0



using namespace std;
using namespace cv;




vector<Mat> wavelet(Mat im)
{
    float a,b,c,d,e,f;
    Mat im1, im2, im3, im4, im5, im6;
    Mat imi=Mat::zeros(im.rows,im.cols,CV_8U);
    im.copyTo(imi);
    im.convertTo(im,CV_32F,1.0,0.0);
    im1=Mat::zeros(im.rows/4,im.cols,CV_32F);
    im2=Mat::zeros(im.rows/4,im.cols,CV_32F);
    im3=Mat::zeros(im.rows/4,im.cols/4,CV_32F);
    im4=Mat::zeros(im.rows/4,im.cols/4,CV_32F);
    im5=Mat::zeros(im.rows/4,im.cols/4,CV_32F);
    im6=Mat::zeros(im.rows/4,im.cols/4,CV_32F);

    for(int rcnt=0;rcnt+3<im.rows;rcnt+=4)
    {
        for(int ccnt=0;ccnt<im.cols;ccnt++)
        {


            a=im.at<float>(rcnt,ccnt);
            b=im.at<float>(rcnt+1,ccnt);
            c=im.at<float>(rcnt+2,ccnt);
            d=im.at<float>(rcnt+3,ccnt);
            e=(a*h0)+(b*h1)+(c*h2)+(d*h3);
            f=(a*g0)+(b*g1)+(c*g2)+(d*g3);
            int _rcnt=rcnt/4;
            im1.at<float>(_rcnt,ccnt)=e;
            im2.at<float>(_rcnt,ccnt)=f;
        }
    }

    for(int rcnt=0;rcnt<im.rows/4;rcnt++)
    {
        for(int ccnt=0;ccnt+3<im.cols;ccnt+=4)
        {

            a=im1.at<float>(rcnt,ccnt);
            b=im1.at<float>(rcnt,ccnt+1);
            c=im1.at<float>(rcnt,ccnt+2);
            d=im1.at<float>(rcnt,ccnt+3);
            e=(a*h0)+(b*h1)+(c*h2)+(d*h3);
            f=(a*g0)+(b*g1)+(c*g2)+(d*g3);
            int _ccnt=ccnt/4;
            im3.at<float>(rcnt,_ccnt)=e;
            im4.at<float>(rcnt,_ccnt)=f;
        }
    }

    for(int rcnt=0;rcnt<im.rows/4;rcnt++)
    {
        for(int ccnt=0;ccnt+3<im.cols;ccnt+=4)
        {

            a=im2.at<float>(rcnt,ccnt);
            b=im2.at<float>(rcnt,ccnt+1);
            c=im2.at<float>(rcnt,ccnt+2);
            d=im2.at<float>(rcnt,ccnt+3);
            e=(a*h0)+(b*h1)+(c*h2)+(d*h3);
            f=(a*g0)+(b*g1)+(c*g2)+(d*g3);
            int _ccnt=ccnt/4;
            im5.at<float>(rcnt,_ccnt)=e;
            im6.at<float>(rcnt,_ccnt)=f;
        }
    }

    Mat LL = Mat(im3);
    Mat LH = Mat(im4);
    Mat HL = Mat(im5);
    Mat HH = Mat(im6);
    LL.convertTo(LL,CV_8U);
    LH.convertTo(LH,CV_8U);
    HL.convertTo(HL,CV_8U);     
    HH.convertTo(HH,CV_8U); 

    vector<Mat> elements;
    elements.push_back(LL);
    elements.push_back(LH);
    elements.push_back(HL);
    elements.push_back(HH);
    return elements;

}

int main(int argc, char **argv)
{
    Mat image = imread(argv[1],0);
    vector<Mat> subbands = wavelet(image);
    int rows = subbands[0].rows;
    int cols = subbands[0].cols;
    Mat energy(rows,cols,CV_8UC1);
    for (int i=0;i<rows;i++)
    {
        for (int j=0;j<cols;j++)
        {
            int x=subbands[1].at<uchar>(i,j);
            int y=subbands[2].at<uchar>(i,j);
            int z=subbands[3].at<uchar>(i,j);
            energy.at<uchar>(i,j)=sqrt(x*x+y*y+z*z);
        }
    }



    imshow("energy",energy);
    waitKey(0);
}