HOG特征提取代码（opencv处理基本数据,c语言实现基本算法）

#include<cv.h>

#include<highgui.h>

#include<math.h>

#include<opencv.hpp>

using namespace cv;

using namespace std;

IplImage * GRBtoGrey(IplImage* img)//RGB图像转为灰度图像

{

    IplImage* dest=cvCreateImage(cvSize(img->width, img->height),img->depth,1);

    uchar* data = (uchar*)img->imageData;

    int b,g,r;

    for(int i = 0;i<img->height;i++){

        for(int j = 0;j<img->width;j++){

            b = data[i*img->widthStep+j*img->nChannels+0];

            g = data[i*img->widthStep+j*img->nChannels+1];

            r = data[i*img->widthStep+j*img->nChannels+2];

            ((uchar*)(dest->imageData+i*dest->widthStep))[j]=0.3*r+0.59*g+0.11*b;

        }

    }

    return dest;

}

IplImage* nomolize(IplImage *img)//必须是灰度图

{

    uchar* gM = (uchar*)img->imageData;

    int max = 0,min = 255;

    for(int i = 0;i<img->height;i++){

        for(int j = 0;j<img->width;j++){

            int num=gM[i*img->widthStep+j*img->nChannels];

            if(num>max){

                max = num;

            }

            if(num<min){

                min = num;

            }

        }

    }

    for(int i = 0;i<img->height;i++){

        for(int j = 0;j<img->width;j++){

            int num = (int)(float)(gM[i*img->widthStep+j*img->nChannels]-min)*

            ((float)(255)/(float)(max-min));

            if(num>255){

                num = 255;

            }

            ((uchar*)(img->imageData+i*img->widthStep))[j] = num;

        }

    }

    return img;

}

IplImage *greygamma(IplImage *greyimage){

    IplImage *gammaimage = cvCreateImage(cvSize(greyimage->width,greyimage->height),

                                         greyimage->depth,greyimage->nChannels);

    uchar* data = (uchar*)greyimage->imageData;

    for(int i = 0;i<greyimage->height;i++){

        for(int j = 0;j<greyimage->width;j++){

            int gamma=data[i*greyimage->widthStep+j*greyimage->nChannels];

            ((uchar*)(gammaimage->imageData+i*gammaimage->widthStep))[j] = (int)sqrt((float)gamma);

        }

    }

    return nomolize(gammaimage);

}

IplImage *gradientimg(IplImage *img){

    uchar * data = (uchar*)img->imageData;

    for(int i = 1;i<img->height-1;i++){

        for(int j = 1;j<img->width-1;j++){

            int Gx = data[i*img->widthStep+(j+1)*img->nChannels]-data[i*img->widthStep+(j-1)*img->nChannels];

            int Gy = data[(i+1)*img->widthStep+j*img->nChannels]-data[(i-1)*img->widthStep+j*img->nChannels];

            int gradient = (int)sqrt((float)(Gx*Gx+Gy*Gy));

            int theta = (int)(atan((float)Gy/(float)Gx)*180/3.14);

            ((uchar*)(img->imageData+i*img->widthStep))[j] = theta;

        }

    }

    return  nomolize(img);

}

int *CellFeature(IplImage *img ,int w,int h){//8*8 cell

    int cell_w = 8;

    int f_n = 9;

    int *feature = new int[f_n];

    for(int i = 0;i<f_n;i++){

        f_n = 0;

    }

    for(int i = h;i<h+cell_w;i++){

        for(int j = w;j<w+cell_w;j++){

            feature[((uchar*)(img->imageData+i*img->widthStep))[j]/40]++;

        }

    }

    return feature;

}

int *HogFeature(IplImage *img){

    int cell_w = 8;

    int cell_fn = 9;

    int cell_wn = img->width/cell_w;

    int cell_hn = img->height/cell_w;

    int *hog_f = new int[cell_wn*cell_hn*cell_fn];

    int m = 0;

    for(int i = 0;i<cell_hn;i++){

        for(int j = 0;j<cell_wn;j++){

            int *feature = CellFeature(img,j*cell_w,i);

            for(int k = 0;k<cell_fn;k++){

                hog_f[m++] = feature[k];

            }

        }

    }

    for(int i = 0;i<cell_wn*cell_hn*cell_fn;i++){

        if(i%9==0){

            printf("\n");

        }

        if(i%(2*2*9)==0){

            printf("-------------------------------------\n\n");

        }

        printf("%d ",hog_f[i]);

    }

    return hog_f;

}

int main()

{

    IplImage *img=cvLoadImage("Img2.jpg");

    if(img==NULL){

        printf("
9e02
img is null");

        return 0;

    }

    //cvNamedWindow("greyimage");

    IplImage* greyimg = GRBtoGrey(img);

    //cvShowImage("greyimage",greyimg);

    //cvWaitKey();

    //cvNamedWindow("gammaimage");

    IplImage* gammaimg = greygamma(greyimg);

    //cvShowImage("gammaimage",gammaimg);

    printf("gamma end\n");

    //cvWaitKey();

    //cvNamedWindow("gradientimage");

    IplImage* gradientimage = gradientimg(gammaimg);

    //cvShowImage("gradientimage",gradientimage);

    printf("gradient end\n");

    //cvWaitKey();

    int *hog_f = HogFeature(gradientimage);

    return 1;

}