Hough变换检测直线

直线的霍夫变换：

霍夫空间极坐标与图像空间的转换公式：
p = y * sin(theta) + x * cos(theta);

之后遍历图像的每个坐标点，每个坐标点以一度为增量，求取对应的p值，存入数组中，查找数组中数目大于一定阈值的p和theta，再在图像空间中把 直线 恢复出来

霍夫变换就是把图像左边空间上的线段转换到霍夫空间一个点，然后通过点的数目多少来确定是否为一条线段（但是画出的结果为一条直线）

实现代码如下：

#include <iostream>#include "gdal_priv.h"#include <string>using namespace std;//图像的膨胀//算法的实现依然有重复的地方，会造成空间和时间上的浪费，但是效果还可以，暂定如此，如有好的算法再进行改进void Expand(unsigned char* date,unsigned char* ExpandImage,int Width,int Height){    int x, y;    int Direction[8][2] = {-1, -1, 0, -1, 1, -1, 1, 0, 1, 1, 0, 1, -1, 1, -1, 0};    int Index;    for(int i = 1;i < Height - 1;++i)    {        for(int j = 1;j < Width - 1;++j)        {            if(date[i * Width + j] == 255)            {                for(int k = 0;k < 8;++k)                {                    x = i + Direction[k][0];                    y = j + Direction[k][1];                    Index = x * Width + y;                    ExpandImage[Index] = 255;                }            }        }    }    return;}//图像的腐蚀void Erosion(unsigned char* date,unsigned char* ErosionImage,int Width,int Height){    int x, y;    int Direction[8][2] = {-1, -1, 0, -1, 1, -1, 1, 0, 1, 1, 0, 1, -1, 1, -1, 0};    int Index;    for(int i = 1;i < Height - 1;++i)    {        for(int j = 1;j < Width - 1;++j)        {            if(date[i * Width + j] == 0)            {                for(int k = 0;k < 8;++k)                {                    x = i + Direction[k][0];                    y = j + Direction[k][1];                    Index = x * Width + y;                    ErosionImage[Index] = 0;                }            }        }    }    return;}//图像相减求边界void Subtraction(unsigned char* ResultImage,unsigned char* leftImage,unsigned char* rightImage,int Width,int Height){    int Index;    for(int i = 0;i < Height;++i)        for(int j = 0;j < Width;++j)        {            Index = i * Width + j;            ResultImage[Index] = leftImage[Index] - rightImage[Index];        }    return ;}void FindBoundary(unsigned char* image,unsigned char* tempImage,int Width,int Height){    //生成对于图像膨胀的图像    unsigned char* ExpandImage = new unsigned char[Width * Height];    memset(ExpandImage,0,sizeof(unsigned char) * Width * Height);    Expand(image ,ExpandImage,Width ,Height);    Subtraction(tempImage,ExpandImage,image,Width,Height);}/************************************************************************** 直线的Hough检测* 参数：image0为原图形，image1为边缘检测结果，w、h为图像的宽和高* 由于得到的Hough变换结果图像与原图像大小不同，为了得到新的宽高信息* w、h使用引用类型*************************************************************************/unsigned char** HoughLine(unsigned char* image0, unsigned char* &tempImage, int &Width, int &Height,int scale=1){    //定义三角函数表    double sinValue[360];    double cosValue[360];    int i,x,y;    int k = 100;    int p = (int)(sqrt((double)(Width * Width + Height * Height) + 1));   //计算对角线长度    //申请临时存储空间 用来保存边缘检测结果//  tempImage = new unsigned char[Width * Height];    memset(tempImage,0,sizeof(unsigned char) * Width * Height);    //边缘检测//  SideGrandiant(image0, tempImage, Width, Height);    FindBoundary(image0, tempImage, Width, Height);//  //根据Hough变换结果图的大小 重新为输出图象分配空间//  if(image1 != NULL) //      delete image1;//////    image1 = (BYTE*)malloc(sizeof(BYTE)*p*360*4);////  image1 = new unsigned char[p * 360];//  memset(image1,0,p * 360);    //将图像转换为矩阵形式//  BYTE** HoughBuf =CreatImage(image1,360,p);    unsigned char** HoughBuf = new unsigned char* [p];    for(int i = 0;i < p;++i)    {        HoughBuf[i] = new unsigned char[360];        memset(HoughBuf[i],0,sizeof(unsigned char) * 360);        //HoughBuf[i] = image1 + i * 360;    }    //for(int i = 0;i < p;++i)    //{    //  for(int j = 0;j < 360;++j)    //      HoughBuf[i][j] = image1[i * 360 + j];    //}    //计算三角函数表    for(i=0; i<360 ; i++)    {        sinValue[i] = sin(i*3.1415926/180);        cosValue[i] = cos(i*3.1415926/180);    }    int tp;    //遍历原图象中的每个像素    for(y = 0; y < Height; y++)        for(x = 0; x < Width; x++)        {            //对经过当前像素的任何直线区域进行检测            for(i = 0; i < 360; i++)            {                if( tempImage[(y * Width + x)] > k )                {                    tp = (int)( x * sinValue[i] + y * cosValue[i]);                    //忽略负数同时防止计数器溢出                    if (tp < 0 || HoughBuf[tp][i] == 255) continue;                    HoughBuf[tp][i] += scale;                }            }        }    //重新设定图象大小    //Width = 360;    //Height = p;//  delete tempImage;    return HoughBuf;}//画检测到的直线void DrawLine(unsigned char* LineIamge,int Width,int Height,int p,int theta){    double k,b;    int x,y;    if(theta != 90)    //如果斜率存在    {        //计算直线方程的参数        b = p / cos(theta * 3.1415926535 / 180);        k = -sin(theta * 3.1415926535 / 180) / cos(theta * 3.1415926535 / 180);        y=0;        x=0;        //斜率小于1的情况        if(abs(k) <= 1)        {            for(x = 0;x < Width;x++)            {                y=(int)(k * x + b);                if(y >= 0 && y < Height)                {                    LineIamge[y * Width + x] = 255;                }            }        }        //斜率大于1的情况        else        {            for(y = 0;y < Height;y++)            {                x = (int)(y / k - b / k);                if(x >= 0 && x < Width)                {                    /*imageBuf[y][x*4]=255;                    imageBuf[y][x*4+1]=0;                    imageBuf[y][x*4+2]=0;                    imageBuf[y][x*4+3]=255;*/                    LineIamge[y * Width + x] = 255;                }            }        }    }    //斜率不存在的情况    else    {        for(y = 0; y < Height;y++)        {            /*imageBuf[y][p*4]=255;            imageBuf[y][p*4+1]=0;            imageBuf[y][p*4+2]=0;            imageBuf[y][p*4+3]=255;*/            LineIamge[y * Width + p] = 255;        }    }}int main(){    GDALAllRegister();    CPLSetConfigOption("GDAL_FILENAME_IS_UTF8","NO");    string str1="1.1.bmp";    string str2="1.2.tif";    string str3 = "1.3.tif";    GDALDataset* pInDataset=(GDALDataset*)GDALOpen(str1.data() ,GA_ReadOnly);    if(pInDataset == nullptr)    {        cout<<"未找到输入图像"<<endl;        getchar();        return 1;    }    int Width=pInDataset->GetRasterXSize();    int Height = pInDataset->GetRasterYSize();    int band = pInDataset->GetRasterCount();    double dGeoTrans[6]={};    pInDataset->GetGeoTransform(dGeoTrans);    const char* cProjectionRef = pInDataset->GetProjectionRef();    unsigned char* Image = new unsigned char[Width * Height];    GDALRasterBand* pRasterBand = pInDataset->GetRasterBand(1);    CPLErr err=pRasterBand->RasterIO(GF_Read ,0 ,0 ,Width ,Height ,Image ,Width ,Height ,GDT_Byte ,0,0);    unsigned char* ResultImage = new unsigned char[Width * Height];//保存图像的边缘信息，通过膨胀后的图像减去原始图像得到的边缘图像，用来检测是否得到了边缘    //ResultImage = nullptr;    //unsigned char** HoughBuf = nullptr;    unsigned char** HoughBuf;    HoughBuf = HoughLine(Image,ResultImage,Width,Height);    GDALDriver* pDriver = GetGDALDriverManager()->GetDriverByName("GTiff");    GDALDataset* pOutDataset = pDriver->Create("1.2.tif" ,Width ,Height ,1 ,GDT_Byte ,NULL);    GDALRasterBand* pOutRasterband=pOutDataset->GetRasterBand(1);    pOutRasterband->RasterIO(GF_Write ,0 ,0 ,Width ,Height ,ResultImage ,Width ,Height ,GDT_Byte ,0 ,0);    int p = (int)(sqrt((double)(Width * Width + Height * Height) + 1));   //计算对角线长度    unsigned char* LineImage = new unsigned char[Width * Height];    memset(LineImage,0,sizeof(unsigned char) * Width * Height);    if(HoughBuf != nullptr)        for(int i = 0;i < p;++i)        {            for(int j = 0;j < 360;++j)            {                if(HoughBuf[i][j] > 200)        //设置阈值为200，可自行设置                {                    cout<<(int)HoughBuf[i][j]<<" ";                    DrawLine(LineImage,Width,Height,i,j);//得到的结果为一条直线                }            }            cout<<"***************"<<endl;        }    GDALDriver* pLineDriver = GetGDALDriverManager()->GetDriverByName("GTiff");    GDALDataset* pOutLineDataset = pLineDriver->Create("1.3.tif" ,Width ,Height ,1 ,GDT_Byte ,NULL);    GDALRasterBand* pOutLineRasterband=pOutLineDataset->GetRasterBand(1);    pOutLineRasterband->RasterIO(GF_Write ,0 ,0 ,Width ,Height ,LineImage ,Width ,Height ,GDT_Byte ,0 ,0);    delete Image;    delete ResultImage;    delete LineImage;    for(int i = 0;i < p;++i)        delete HoughBuf[i];    delete HoughBuf;    GDALClose(pOutDataset);    GDALClose(pInDataset);    GDALClose(pOutLineDataset);    GetGDALDriverManager()->DeregisterDriver(pDriver);    GetGDALDriverManager()->DeregisterDriver(pLineDriver);    system("pause");    return 0;}