几种常见的阈值分割算法核心代码.doc

阈值分割1 /*=图像分割=*/2 /*-*/3 /*手动设置阀值*/4 IplImage* binaryImg = cvCreateImage(cvSize(w, h),IPL_DEPTH_8U, 1);5 cvThreshold(smoothImgGauss,binaryImg,71,255,CV_THRESH_BINARY); 6 cvNamedWindow(cvThreshold, CV_WINDOW_AUTOSIZE );7 cvShowImage( cvThreshold, binaryImg );8 /cvReleaseImage(&binaryImg); 9 /*-*/10 /*自适应阀值 /计算像域邻域的平均灰度，来决定二值化的值*/11 IplImage* adThresImg = cvCreateImage(cvSize(w, h),IPL_DEPTH_8U, 1);12 double max_value=255;13 int adpative_method=CV_ADAPTIVE_THRESH_GAUSSIAN_C;/CV_ADAPTIVE_THRESH_MEAN_C14 int threshold_type=CV_THRESH_BINARY;15 int block_size=3;/阈值的象素邻域大小16 int offset=5;/窗口尺寸17 cvAdaptiveThreshold(smoothImgGauss,adThresImg,max_value,adpative_method,threshold_type,block_size,offset);18 cvNamedWindow(cvAdaptiveThreshold, CV_WINDOW_AUTOSIZE );19 cvShowImage( cvAdaptiveThreshold, adThresImg );20 cvReleaseImage(&adThresImg);21 /*-*/22 /*最大熵阀值分割法*/ 23 IplImage* imgMaxEntropy = cvCreateImage(cvGetSize(imgGrey),IPL_DEPTH_8U,1);24 MaxEntropy(smoothImgGauss,imgMaxEntropy);25 cvNamedWindow(MaxEntroyThreshold, CV_WINDOW_AUTOSIZE );26 cvShowImage( MaxEntroyThreshold, imgMaxEntropy );/显示图像27 cvReleaseImage(&imgMaxEntropy ); 28 /*-*/29 /*基本全局阀值法*/30 IplImage* imgBasicGlobalThreshold = cvCreateImage(cvGetSize(imgGrey),IPL_DEPTH_8U,1);31 cvCopyImage(srcImgGrey,imgBasicGlobalThreshold);32 int pg256,i,thre; 33 for (i=0;i256;i+) pgi=0;34 for (i=0;iimageSize;i+) / 直方图统计35 pg(BYTE)imgBasicGlobalThreshold-imageDatai+; 36 thre = BasicGlobalThreshold(pg,0,256); / 确定阈值37 coutThe Threshold of this Image in BasicGlobalThreshold is:threendl;/输出显示阀值38 cvThreshold(imgBasicGlobalThreshold,imgBasicGlobalThreshold,thre,255,CV_THRESH_BINARY); / 二值化 39 cvNamedWindow(BasicGlobalThreshold, CV_WINDOW_AUTOSIZE );40 cvShowImage( BasicGlobalThreshold, imgBasicGlobalThreshold);/显示图像41 cvReleaseImage(&imgBasicGlobalThreshold);42 /*-*/43 /*OTSU*/44 IplImage* imgOtsu = cvCreateImage(cvGetSize(imgGrey),IPL_DEPTH_8U,1);45 cvCopyImage(srcImgGrey,imgOtsu);46 int thre2;47 thre2 = otsu2(imgOtsu);48 coutThe Threshold of this Image in Otsu is:thre2endl;/输出显示阀值49 cvThreshold(imgOtsu,imgOtsu,thre2,255,CV_THRESH_BINARY); / 二值化 50 cvNamedWindow(imgOtsu, CV_WINDOW_AUTOSIZE );51 cvShowImage( imgOtsu, imgOtsu);/显示图像 52 cvReleaseImage(&imgOtsu);53 /*-*/54 /*上下阀值法：利用正态分布求可信区间*/55 IplImage* imgTopDown = cvCreateImage( cvGetSize(imgGrey), IPL_DEPTH_8U, 1 );56 cvCopyImage(srcImgGrey,imgTopDown);57 CvScalar mean ,std_dev;/平均值、 标准差58 double u_threshold,d_threshold;59 cvAvgSdv(imgTopDown,&mean,&std_dev,NULL); 60 u_threshold = mean.val0 +2.5* std_dev.val0;/上阀值61 d_threshold = mean.val0 -2.5* std_dev.val0;/下阀值62 /u_threshold = mean + 2.5 * std_dev; /错误63 /d_threshold = mean - 2.5 * std_dev;64 coutThe TopThreshold of this Image in TopDown is:d_thresholdendl;/输出显示阀值65 coutThe DownThreshold of this Image in TopDown is:u_thresholdendl;66 cvThreshold(imgTopDown,imgTopDown,d_threshold,u_threshold,CV_THRESH_BINARY_INV);/上下阀值67 cvNamedWindow(imgTopDown, CV_WINDOW_AUTOSIZE );68 cvShowImage( imgTopDown, imgTopDown);/显示图像 69 cvReleaseImage(&imgTopDown);70 /*-*/71 /*迭代法*/72 IplImage* imgIteration = cvCreateImage( cvGetSize(imgGrey), IPL_DEPTH_8U, 1 );73 cvCopyImage(srcImgGrey,imgIteration);74 int thre3,nDiffRec;75 thre3 =DetectThreshold(imgIteration, 100, nDiffRec);76 coutThe Threshold of this Image in imgIteration is:thre3height;9 int width = img-width;10 int step = img-widthStep/sizeof(uchar);11 uchar *data = (uchar*)img-imageData;12 13 iDiffRec =0;14 int F256= 0 ; /直方图数组15 int iTotalGray=0;/灰度值和16 int iTotalPixel =0;/像素数和17 byte bt;/某点的像素值18 19 uchar iThrehold,iNewThrehold;/阀值、新阀值20 uchar iMaxGrayValue=0,iMinGrayValue=255;/原图像中的最大灰度值和最小灰度值21 uchar iMeanGrayValue1,iMeanGrayValue2;22 23 /获取(i,j)的值，存于直方图数组F24 for(int i=0;iwidth;i+)25 26 for(int j=0;jheight;j+)27 28 bt = datai*step+j;29 if(btiMaxGrayValue)32 iMaxGrayValue = bt;33 Fbt+;34 35 36 37 iThrehold =0;/38 iNewThrehold = (iMinGrayValue+iMaxGrayValue)/2;/初始阀值39 iDiffRec = iMaxGrayValue - iMinGrayValue;40 41 for(int a=0;(abs(iThrehold-iNewThrehold)0.5)&anMaxIter;a+)/迭代中止条件42 43 iThrehold = iNewThrehold;44 /小于当前阀值部分的平均灰度值45 for(int i=iMinGrayValue;iiThrehold;i+)46 47 iTotalGray += Fi*i;/F存储图像信息48 iTotalPixel += Fi;49 50 iMeanGrayValue1 = (uchar)(iTotalGray/iTotalPixel);51 /大于当前阀值部分的平均灰度值52 iTotalPixel =0;53 iTotalGray =0;54 for(int j=iThrehold+1;jiMaxGrayValue;j+)55 56 iTotalGray += Fj*j;/F存储图像信息57 iTotalPixel += Fj; 58 59 iMeanGrayValue2 = (uchar)(iTotalGray/iTotalPixel);60 61 iNewThrehold = (iMeanGrayValue2+iMeanGrayValue1)/2; /新阀值62 iDiffRec = abs(iMeanGrayValue2 - iMeanGrayValue1);63 64 65 /coutThe Threshold of this Image in imgIteration is:iThreholdendl;66 return iThrehold;67 68Otsu代码一1 /*=*/2 /* OTSU global thresholding routine */3 /* takes a 2D unsigned char array pointer, number of rows, and */4 /* number of cols in the array. returns the value of the threshold */5 /*parameter: 6 *image - buffer for image7 rows, cols - size of image8 x0, y0, dx, dy - region of vector used for computing threshold9 vvv - debug option, is 0, no debug information outputed10 */11 /*12 OTSU 算法可以说是自适应计算单阈值（用来转换灰度图像为二值图像）的简单高效方法。13 下面的代码最早由 Ryan Dibble提供，此后经过多人Joerg.Schulenburg, R.Z.Liu 等修改，补正。14 算法对输入的灰度图像的直方图进行分析，将直方图分成两个部分，使得两部分之间的距离最大。15 划分点就是求得的阈值。16 */17 /*=*/18 int otsu (unsigned char*image, int rows, int cols, int x0, int y0, int dx, int dy, int vvv)19 20 21 unsigned char*np; / 图像指针22 int thresholdValue=1; / 阈值23 int ihist256; / 图像直方图，256个点24 25 int i, j, k; / various counters26 int n, n1, n2, gmin, gmax;27 double m1, m2, sum, csum, fmax, sb;28 29 / 对直方图置零30 memset(ihist, 0, sizeof(ihist);31 32 gmin=255; gmax=0;33 / 生成直方图34 for (i = y0 +1; i y0 + dy -1; i+) 35 36 np = (unsigned char*)imagei*cols+x0+1;37 for (j = x0 +1; j gmax) gmax=*np;41 if(*np gmin) gmin=*np;42 np+; /* next pixel */43 44 45 46 / set up everything47 sum = csum =0.0;48 n =0;49 50 for (k =0; k =255; k+) 51 52 sum += (double) k * (double) ihistk; /* x*f(x) 质量矩*/53 n += ihistk; /* f(x) 质量 */54 55 56 if (!n) 57 58 / if n has no value, there is problems.59 fprintf (stderr, NOT NORMAL thresholdValue = 160n);60 return (160);61 62 63 / do the otsu global thresholding method64 fmax =-1.0;65 n1 =0;66 for (k =0; k fmax) 84 85 fmax = sb;86 thresholdValue = k;87 88 89 90 / at this point we have our thresholding value91 92 / debug code to display thresholding values93 if ( vvv &1 )94 fprintf(stderr,# OTSU: thresholdValue = %d gmin=%d gmax=%dn,95 thresholdValue, gmin, gmax);96 97 return(thresholdValue);98 Otsu代码二1 /*=*/2 /* OTSU global thresholding routine */3 /*=*/4 int otsu2 (IplImage *image)5 6 int w = image-width;7 int h = image-height;8 9 unsigned char*np; / 图像指针10 unsigned char pixel;11 int thresholdValue=1; / 阈值12 int ihist256; / 图像直方图，256个点13 14 int i, j, k; / various counters15 int n, n1, n2, gmin, gmax;16 double m1, m2, sum, csum, fmax, sb;17 18 / 对直方图置零.19 memset(ihist, 0, sizeof(ihist);20 21 gmin=255; gmax=0;22 / 生成直方图23 for (i =0; i imageData + image-widthStep*i);26 for (j =0; j gmax) gmax= pixel;31 if(pixel gmin) gmin= pixel;32 33 34 35 / set up everything36 sum = csum =0.0;37 n =0;38 39 for (k =0; k =255; k+) 40 41 sum += k * ihistk; /* x*f(x) 质量矩*/42 n += ihistk; /* f(x) 质量 */43 44 45 if (!n) 46 47 / if n has no value, there is problems.48 /fprintf (stderr, NOT NORMAL thresholdValue = 160n);49 thresholdValue =160;50 goto L;51 52 53 / do the otsu global thresholding method54 fmax =-1.0;55 n1 =0;56 for (k =0; k fmax)68 69 fmax = sb;70 thresholdValue = k;71 72 73 74 L:75 for (i =0; i imageData + image-widthStep*i);78 for (j =0; j = thresholdValue)81 npj =255;82 else npj =0;83 84 85 86 /coutThe Threshold of this Image in Otsu is:thresholdValueendl;87 return(thresholdValue);88 最大熵阀值1 /*=2 = 代码内容：最大熵阈值分割 3 = 修改日期:2009-3-3 4 = 作者:crond123 5 = 博客:/crond123/6 = E_Mail: 7 =*/8 / 计算当前位置的能量熵9 double caculateCurrentEntropy(CvHistogram * Histogram1,int cur_threshold,entropy_state state)10 11 int start,end;12 int total =0;13 double cur_entropy =0.0;14 if(state = back) 15 16 start =0;17 end = cur_threshold; 18 19 else 20 21 start = cur_threshold;22 end =256; 23 24 for(int i=start;iend;i+) 25 26 total += (int)cvQueryHistValue_1D(Histogram1,i);/查询直方块的值 P30427 28 for(int j=start;jdepth =8& dst-depth =8);47 assert(src-nChannels =1);48 CvHistogram * hist = cvCreateHist(1,&HistogramBins,CV_HIST_ARRAY,HistogramRange);/创建一个指定尺寸的直方图49 /参数含义：直方图包含的维数、直方图维数尺寸的数组、直方图的表示格式、方块范围数组、归一化标志50 cvCalcHist(&src,hist);/计算直方图51 d