基于Haar小波变换和KNN算法的DSP人脸识别代码

/******************************************宏定义begin************************************************/ #define IMAGEWIDTH 32//图像宽度 #define IMAGEHEIGHT 32//图像高度 #define LENGTH 32//图像进行一维harr变换时的长度，相当于图像宽度和高度 //来自例程文件，说明哪些图片 #define MODEPHOTO00 1 #define MODEPHOTO01 2 #define MODEPHOTO02 3 #define MODEPHOTO03 4 #define MODEPHOTO04 5 #define MODEPHOTO05 6 #define MODEPHOTO06 7 #define MODEPHOTO07 8 #define MODEPHOTO10 9 #define MODEPHOTO11 10 #define MODEPHOTO12 11 #define MODEPHOTO13 12 #define MODEPHOTO14 13 #define MODEPHOTO15 14 #define MODEPHOTO16 15 #define MODEPHOTO17 16 #define MODEPHOTO20 17 #define MODEPHOTO21 18 #define MODEPHOTO22 19 #define MODEPHOTO23 20 #define MODEPHOTO24 21 #define MODEPHOTO25 22 #define MODEPHOTO26 23 #define MODEPHOTO27 24 #define MODEPHOTO30 25 #define MODEPHOTO31 26 #define MODEPHOTO32 27 #define MODEPHOTO33 28 #define MODEPHOTO34 29 #define MODEPHOTO35 30 #define MODEPHOTO36 31 #define MODEPHOTO37 32 #define MODEPHOTO40 33 #define MODEPHOTO41 34 #define MODEPHOTO42 35 #define MODEPHOTO43 36 #define MODEPHOTO44 37 #define MODEPHOTO45 38 #define MODEPHOTO46 39 #define MODEPHOTO47 40 //#define TESTMATRIX 101 #define TRAINPHOTO00 101 #define TRAINPHOTO01 102 #define TRAINPHOTO02 103 #define TRAINPHOTO10 104 #define TRAINPHOTO11 105 #define TRAINPHOTO12 106 #define TRAINPHOTO20 107 #define TRAINPHOTO21 108 #define TRAINPHOTO22 109 #define TRAINPHOTO30 110 #define TRAINPHOTO31 111 #define TRAINPHOTO32 112 #define TRAINPHOTO40 113 #define TRAINPHOTO41 114 #define TRAINPHOTO42 115 #define GRAYBARLEVEL 16 /******************************************宏定义end************************************************/ void InitImage(unsigned int nMode,unsigned char *pImage,int nWidth,int nHeight); void conv(float* f,float* g,float* y,int length); void haarone(float *input,float *output,int length); void FloatImage(unsigned char *pImage,float *qImage,int nWidth,int nHeight); void UcharImage(float *pImage,unsigned char *qImage,int nWidth,int nHeight); void AddImage(float *pImage,int nWidth,int nHeight); void CopyImage(float *pImage,float *qImage,int nWidth,int nHeight); void MinImage(float *pImage,float *qImage,int nWidth,int nHeight); void MaxImage(float *pImage,float *qImage,int nWidth,int nHeight); unsigned int imageIndex[5][8]; unsigned int trainIndex[5][3]; unsigned char dbImage[IMAGEWIDTH*IMAGEHEIGHT];//输入图像 float outImage[IMAGEWIDTH][IMAGEHEIGHT];//输出图像 float changeImage[IMAGEWIDTH][IMAGEHEIGHT];//中间变量1 float nextImage[IMAGEWIDTH][IMAGEHEIGHT];//中间变量2 float endImage[IMAGEWIDTH/2][IMAGEHEIGHT/2]; int label[40]={1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5}; //unsigned char outcharImage[IMAGEWIDTH][IMAGEHEIGHT];//输出图像 //unsigned char changecharImage[IMAGEWIDTH][IMAGEHEIGHT];//中间变量1 //unsigned char nextcharImage[IMAGEWIDTH][IMAGEHEIGHT];//中间变量2 //定义所有图像的Harr特征数组 unsigned char endcharImage[40][IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char trainImage[15][IMAGEWIDTH/2][IMAGEHEIGHT/2]; /* unsigned char endcharImage00[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage01[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage02[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage03[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage04[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage05[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage06[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage07[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage10[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage11[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage12[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage13[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage14[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage15[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage16[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage17[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage20[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage21[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage22[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage23[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage24[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage25[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage26[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage27[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage30[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage31[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage32[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage33[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage34[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage35[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage36[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage37[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage40[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage41[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage42[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage43[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage44[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage45[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage46[IMAGEWIDTH/2][IMAGEHEIGHT/2]; unsigned char endcharImage47[IMAGEWIDTH/2][IMAGEHEIGHT/2]; */ float index[LENGTH]; float outdex[LENGTH]; int result[5][3]; int main() { int i,j,m,n; int a,b; int raw,col;//定义行和列变量 m=1; n=101; raw=IMAGEWIDTH; col=IMAGEHEIGHT; for(i=0;i<5;i++) for(j=0;j<8;j++) { imageIndex[i][j]= m; m++; }//设置图像索引数组 for(a=0;a<5;a++) for(b=0;b<8;b++) { InitImage(imageIndex[a][b],dbImage,IMAGEWIDTH,IMAGEHEIGHT);//读入图像 FloatImage(dbImage,*changeImage,IMAGEWIDTH,IMAGEHEIGHT);//强制转换为float型 for(i=0;i<col;i++) { for(j=0;j<raw;j++) { index[j]=changeImage[j][i]; } haarone(index,outdex,LENGTH); for(j=0;j<raw;j++) { changeImage[j][i]=outdex[j]; } }//对所有列进行harr变换 for(i=0;i<raw;i++) { for(j=0;j<col;j++) { index[j]=changeImage[i][j]; } haarone(index,outdex,LENGTH); for(j=0;j<col;j++) { changeImage[i][j]=outdex[j]; } } //对图像进行归一化，经过归一化之后轨迹主要在左上角方格的右下角中，大小为32*32 MinImage(*changeImage,*nextImage,IMAGEWIDTH,IMAGEHEIGHT); MaxImage(*nextImage,*outImage,IMAGEWIDTH,IMAGEHEIGHT); //特征存入endImage数组中并输出 /* AddImage(*changeImage,IMAGEWIDTH,IMAGEHEIGHT); UcharImage(*changeImage,*changecharImage,IMAGEWIDTH,IMAGEHEIGHT);//强制转换为float型//对所有的行进行harr变化 UcharImage(*outImage,*outcharImage,IMAGEWIDTH,IMAGEHEIGHT);//强制转换为float型//对所有的行进行harr变化 */ for(i=IMAGEHEIGHT/2;i<IMAGEHEIGHT;i++) { for(j=0;j<IMAGEWIDTH/2;j++) { endImage[i-IMAGEWIDTH/2][j]=outImage[i][j]; //printf("%f\t",endImage[i-IMAGEWIDTH/4][j]); } //printf("\n"); } UcharImage(*endImage,*(endcharImage[8*a+b]),IMAGEWIDTH/2,IMAGEHEIGHT/2);//强制转换为float型//对所有的行进行harr变化 /* switch (imageIndex[a][b]) { case MODEPHOTO00: UcharImage(*endImage,*endcharImage00,IMAGEWIDTH/2,IMAGEHEIGHT/2);//强制转换为float型//对所有的行进行harr变化 break; case MODEPHOTO01: UcharImage(*endImage,*endcharImage01,IMAGEWIDTH/2,IMAGEHEIGHT/2);//强制转换为float型//对所有的行进行harr变化 break; case MODEPHOTO02: UcharImage(*endImage,*endcharImage02,IMAGEWIDTH/2,IMAGEHEIGHT/2);//强制转换为float型//对所有的行进行harr变化 break; case MODEPHOTO03: UcharImage(*endImage,*endcharImage03,IMAGEWIDTH/2,IMAGEHEIGHT