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图像处理|【图像处理】DibImage图像处理常用算子

编程语言图像处理




// DibImage.h: interface for the CDibImage class. // //#if !defined(AFX_DIBIMAGE_H__7DE2EE87_190A_4BFD_BBF3_CCC615C53419__INCLUDED_) #define AFX_DIBIMAGE_H__7DE2EE87_190A_4BFD_BBF3_CCC615C53419__INCLUDED_#if _MSC_VER > 1000 #pragma once #endif // _MSC_VER > 1000#definePos(i,j)((i)*Width + j) //#definePosBuf(i,j) (54+sizeof(RGBQUAD)*256 +i*Width + j)typedef struct { int Height; int Width; }Point; class CDibImage { public: CDibImage(); virtual ~CDibImage(); public:/* BYTE *pBuffer ——为图像的灰度数据区域； */ void Filter(BYTE *pBuffer, int MinValue, int MaxValue, int Height, int Width); //设置最大最小值 void FilterBuffer(BYTE *pBuffer, int MinValue, int MaxValue, int Height, int Width); //设置最大最小值 void RemoveBlack(BYTE *pBuffer, int nLianTong, int nSetValue, const int Height , const int Width); //消除杂质灰点 void MidFilter(BYTE *pBuffer, int nNumber, int Height, int Width); //中值滤波 void Averary(BYTE *pBuffer, int Height, int Width); //均值滤波 void Filter124(BYTE *pBuffer, int Height, int Width); //3*3的加权中值滤波；中间像素4倍，十字处像素2倍，四角像素1倍 void ChaoXianAverary(BYTE *pBuffer, int nTValue, int Height, int Width); //该点大于周围8点平均值，则平均值赋给该点，否则不变 void JuBuAverary(BYTE *pBuffer, int Height, int Width); //局部平均化 void VertialEdge(BYTE *pBuffer, int Height, int Width); //得到垂直边界Vertial void HorizontalEdge(BYTE *pBuffer, int Height, int Width); //得到水平边界horizontal void GetEdge(BYTE *pBuffer, int Height, int Width); // 得到图像边界//锐化 void SharpenMenXian(BYTE *pBuffer, int nMenXianValue, int Height, int Width); //门限锐化 void SharpenGuDing(BYTE *pBuffer, int nMenXianValue, int Height, int Width); //特定灰度锐化 void SharpenErZhiHua(BYTE *pBuffer, int nMenXianValue, int Height, int Width); //二值化梯度锐化//边缘检测 void EdgeRobert(BYTE *pBuffer, int Height, int Width); //Robert算子 void Edge_Temple(BYTE *pBuffer, int Height, int Width, int TempH, int TempW, int TempMX, int TempMY, float *fpArray, float fTempCoef); //算子的模板（卷积运算） void EdgeSobel(BYTE *pBuffer, int Height, int Width); //Sobel算子 void EdgePrewitt(BYTE *pBuffer, int Height, int Width); //Prewitt算子 void EdgeKrisch(BYTE *pBuffer, int Height, int Width); //Krisch算子 void EdgeGaussLaplacian(BYTE *pBuffer, int Height, int Width); //GaussLaplacian算子//图像阈值分割 void FenGeZhiFangTu(BYTE *pBuffer, float *fTongji, int Height, int Width); //直方图统计 void FenGeYuZhi(BYTE *pBuffer, int nYuZhi, int Height, int Width); // 阈值分割 void FenGeBanYuZhi(BYTE *pBuffer, int nYuZhi, int Height, int Width); //半阈值分割 void FenGeDieDai(BYTE *pBuffer, int Height, int Width); //迭代阈值分割//轮廓提取 void OutlineGet(BYTE *pBuffer, int Height, int Width); //轮廓提取 void OutlineTrack(BYTE *pBuffer, int Height, int Width); //轮廓跟踪//图像的测量（面积、周长） void MeasureBiaoJi(BYTE *pBuffer, int Height, int Width); //对图像区域进行标记 }; #endif // !defined(AFX_DIBIMAGE_H__7DE2EE87_190A_4BFD_BBF3_CCC615C53419__INCLUDED_)





// DibImage.cpp: implementation of the CDibImage class. // //#include "stdafx.h" #include #include #include "HVSnapPnp.h" #include "DibImage.h"#ifdef _DEBUG #undef THIS_FILE static char THIS_FILE[]=__FILE__; #define new DEBUG_NEW #endif// // Construction/Destruction //CDibImage::CDibImage() {}CDibImage::~CDibImage() {}//最大最小值 void CDibImage::Filter(BYTE *pBuffer, int MinValue, int MaxValue, int Height, int Width) { int i,j; for (i=0; i MaxValue) { pBuffer[Pos(i,j)] = 255; } else if (pBuffer[Pos(i,j)] < MinValue) { pBuffer[Pos(i,j)] = 0; } } } }//最大最小值，加白区 void CDibImage::FilterBuffer(BYTE *pBuffer, int MinValue, int MaxValue, int Height, int Width) { int i,j; BYTE *pTemp= new BYTE[Height * Width]; memcpy(pTemp, pBuffer, Height*Width*sizeof(BYTE)); for (i=200; i MaxValue) { pTemp[Pos(i,j)] = 255; } //else if (pData[Pos(i,j)] < MinValue) //{ //pTemp[Pos(i,j)] = 0; //} } } memcpy(pBuffer, pTemp, Height*Width*sizeof(BYTE)); //for (i=0; i<200; i++) //{ //for (j=0; j<500; j++) //{ //pBuffer[Pos(i,j)] = 255; //} //} delete []pTemp; }//均值滤波 void CDibImage::Averary(BYTE *pBuffer, int Height, int Width) { int i,j; int nAverary; BYTE *pTemp = new BYTE[Height * Width]; memcpy(pTemp, 0, Height*Width*sizeof(BYTE)); for (i=200; i MidArray[i+1]) { nSortTemp = MidArray[i]; MidArray[i] = MidArray[i+1]; MidArray[i+1] = nSortTemp; nSort = 1; } } } while (nSort == 1); pTemp[Pos(i,j)] = MidArray[5]; } }//将处理后的pTemp赋给pBuffer memcpy(pBuffer, pTemp, Height*Width*sizeof(BYTE)); delete []pTemp; }/* 功能：消除杂质灰点 参数：nLianTong——4：连通，8连通 nSetValue——设定的周围的灰度平均值*/ void CDibImage::RemoveBlack(BYTE *pBuffer, int nLianTong, int nSetValue, const int Height , const int Width) { int i,j; int n4JunZhi, n8JunZhi; BYTE *pTemp = new BYTE[Height * Width]; memcpy(pTemp, 0, Height*Width*sizeof(BYTE)); if (nLianTong == 4) { for (i=1; i nSetValue) pTemp[Pos(i,j)] = 255; } } } else if (nLianTong == 8) { for (i=1; i nSetValue) pTemp[Pos(i,j)] = 255; } } } else AfxMessageBox("请将参数设为：4 或者 8 ！"); delete []pTemp; }/* //3*3的加权中值滤波；(中间像素4倍，十字处像素2倍，四角像素1倍) / 16; 函数说明： 121 242 121 */ void CDibImage::Filter124(BYTE *pBuffer, int Height, int Width) { int i,j; int nAverary; BYTE *pTemp = new BYTE[Height * Width]; memcpy(pTemp, 0, Height*Width*sizeof(BYTE)); for (i=1; i nTValue */ void CDibImage::ChaoXianAverary(BYTE *pBuffer, int nTValue, int Height, int Width) { int i,j; int nAverary; BYTE *pTemp = new BYTE[Height * Width]; memcpy(pTemp, 0, Height*Width*sizeof(BYTE)); for (i=1; i nTValue) { *(pTemp+i*Width+j) = nAverary; }} } memcpy(pBuffer, pTemp, Height*Width*sizeof(BYTE)); delete []pTemp; }/************************************************************************/ /* 函数：局部平均化 说明：取5*5窗口；选取4个五边形，4个六边形，一个边长为3的正方形 得到它们的平均值跟方差；采用方差最小的进行平均化。 也称为：自适应平滑方法。 */ /************************************************************************/ void CDibImage::JuBuAverary(BYTE *pBuffer, int Height, int Width) //局部平均化 { int i,j,k; //循环变量 float JunZhi[9] = {0,0,0,0,0,0,0,0,0}; //某区域均值 float FangCha[9] = {0,0,0,0,0,0,0,0,0}; //某区域方差 int nData[9] = {0,0,0,0,0,0,0,0,0}; //某区域数据 int Sum = 0; //某区域数据之和 int nNum = 0; //最终选择的区域 float FangChaMin = 0.0; //最小方差 BYTE *pTemp = new BYTE[Height * Width]; //中间缓冲区 memcpy(pTemp, 0, Height*Width*sizeof(BYTE)); for (i=2; i FangCha[k]) { FangChaMin = FangCha[k]; nNum = k; } } pTemp[Pos(i,j)] = (int)(JunZhi[k] + 0.5); } } memcpy(pBuffer, pTemp, Height*Width*sizeof(BYTE)); delete []pTemp; }//得到垂直边界Vertial void CDibImage::VertialEdge(BYTE *pBuffer, int Height, int Width) { int i,j; BYTE *pTemp = new BYTE[Height * Width]; memcpy(pTemp, 0, Height*Width*sizeof(BYTE)); for (i=1; i T)G(i,j) = G(f(i,j)) + 100; else G(i,j) = f(i,j); 公式：G(f(i,j)) = sqrt((f(i,j)-f(i,j-1))*(f(i,j)-f(i,j-1)) + (f(i,j)-f(i-1,j))*(f(i,j)-f(i-1,j))) */ /************************************************************************/void CDibImage::SharpenMenXian(BYTE *pBuffer, int nMenXianValue, int Height, int Width) { int i,j; int nTemp = 0; BYTE *pTemp = new BYTE[Height * Width]; memcpy(pTemp, 0, Height * Width * sizeof(BYTE)); for (i=1; i nMenXianValue)//如果大于门限值（30） { if (nTemp + 100 > 255) pTemp[Pos(i,j)] = 255; else pTemp[Pos(i,j)] = nTemp + 100; } if (nTemp < 30)//如果小于门限值，则将原数据赋给pTemp pTemp[Pos(i,j)] = pBuffer[Pos(i,j)]; } } memcpy(pBuffer, pTemp, Height*Width*sizeof(BYTE)); delete []pTemp; }/************************************************************************/ /* 函数： 给边缘规定灰度（边缘为255） 与SharpenMenXian()差不多；只是超过门限值的直接赋255; 参数：int nMenXianValue——门限值（参考取值：30） 说明：if( G(i,j) > T)G(i,j) = 255; else G(i,j) = f(i,j); 公式：G(f(i,j)) = sqrt((f(i,j)-f(i,j-1))*(f(i,j)-f(i,j-1)) + (f(i,j)-f(i-1,j))*(f(i,j)-f(i-1,j))) */ /************************************************************************/ void CDibImage::SharpenGuDing(BYTE *pBuffer, int nMenXianValue, int Height, int Width) { int i,j; int nTemp = 0; BYTE *pTemp = new BYTE[Height * Width]; memcpy(pTemp, 0, Height * Width * sizeof(BYTE)); for (i=1; i nMenXianValue)//如果大于门限值 pTemp[Pos(i,j)] = 255; else pTemp[Pos(i,j)] = pBuffer[Pos(i,j)]; } } memcpy(pBuffer, pTemp, Height*Width*sizeof(BYTE)); delete []pTemp; }/************************************************************************/ /* 函数： 给边缘规定灰度（边缘为255），其他区域为0； 与SharpenMenXian()差不多；只是超过门限值的直接赋255,其他区域为0; 参数：int nMenXianValue——门限值（参考取值：30） 说明：if( G(i,j) > T)G(i,j) = 255; else G(i,j) = 0; 公式：G(f(i,j)) = sqrt((f(i,j)-f(i,j-1))*(f(i,j)-f(i,j-1)) + (f(i,j)-f(i-1,j))*(f(i,j)-f(i-1,j))) */ /************************************************************************/ void CDibImage::SharpenErZhiHua(BYTE *pBuffer, int nMenXianValue, int Height, int Width) { int i,j; int nTemp = 0; BYTE *pTemp = new BYTE[Height * Width]; memcpy(pTemp, 0, Height * Width * sizeof(BYTE)); for (i=1; i nMenXianValue)//如果大于门限值 pTemp[Pos(i,j)] = 255; else pTemp[Pos(i,j)] = 0; } } memcpy(pBuffer, pTemp, Height*Width*sizeof(BYTE)); delete []pTemp; }/************************************************************************/ /* 函数：边缘检测——Robert算子 公式：G(i,j) = sqrt((f(i,j)-f(i+1,j+1))*((f(i,j)-f(i+1,j+1))+(f(i+1,j)-f(i,j+1))*(f(i+1,j)-f(i,j+1))) 说明：(i,j+1)(i+1,j+1) (i,j)(i+1,j) */ /************************************************************************/ void CDibImage::EdgeRobert(BYTE *pBuffer, int Height, int Width) { int i,j; BYTE *pTemp = new BYTE[Height * Width]; memcpy(pTemp, 0, Height * Width * sizeof(BYTE)); int nRobert[4] = {0,0,0,0}; for (i=0; i255) pTemp[Pos(i,j)] = 255; else pTemp[Pos(i,j)] = (int)(fResoult+0.5); } } } } memcpy(pBuffer, pTemp, Height*Width*sizeof(BYTE)); delete []pTemp; }/************************************************************************/ /* 函数：边缘检测——Sobel算子（索伯尔算子） 说明：调用两个模板进行卷积运算，取较大值；（进行水平、垂直边缘检测） 具有噪声抑制能力，边缘宽度至少为两个像素； 用来提取图像边缘； 模板1：-1-2-1模板2： +10-1 000+20-2 +1+2+1+10-1 */ /************************************************************************/ void CDibImage::EdgeSobel(BYTE *pBuffer, int Height, int Width) { int i,j; int TempH = 3; int TempW = 3; int TempMX = 1; int TempMY = 1; float fTempCoef = 1; float Template[9]; BYTE *pTemp1 = new BYTE[Height * Width]; memcpy(pTemp1, pBuffer, Height * Width * sizeof(BYTE)); BYTE *pTemp2 = new BYTE[Height * Width]; memcpy(pTemp2, pBuffer, Height * Width * sizeof(BYTE)); Template[0] = -1.0; Template[1] = -2.0; Template[2] = -1.0; Template[3] = 0; Template[4] = 0; Template[5] = 0; Template[6] = 1.0; Template[7] = 2.0; Template[8] = 1.0; Edge_Temple(pTemp1,Height,Width,TempH,TempW,TempMX,TempMY,Template,fTempCoef); Template[0] = -1.0; Template[1] = 0; Template[2] = 1.0; Template[3] = -2.0; Template[4] = 0; Template[5] = 2.0; Template[6] = -1.0; Template[7] = 0; Template[8] = 1.0; Edge_Temple(pTemp2,Height,Width,TempH,TempW,TempMX,TempMY,Template,fTempCoef); for (i=0; i pTemp1[Pos(i,j)]) pTemp1[Pos(i,j)] = pTemp2[Pos(i,j)]; } } memcpy(pBuffer, pTemp1, Height*Width*sizeof(BYTE)); delete []pTemp1; delete []pTemp2; }/************************************************************************/ /* 函数：边缘检测——Prewitt算子（普瑞维特算子） 说明：调用两个模板进行卷积运算，取较大值；（进行水平、垂直边缘检测） 具有噪声抑制能力，边缘宽度至少为两个像素； 用来提取图像边缘； 模板1：-1-1-1模板2： +10-1 000+10-1 +1+1+1+10-1 */ /************************************************************************/ void CDibImage::EdgePrewitt(BYTE *pBuffer, int Height, int Width) { int i,j; int TempH = 3; int TempW = 3; int TempMX = 1; int TempMY = 1; float fTempCoef = 1; float Template[9]; BYTE *pTemp1 = new BYTE[Height * Width]; memcpy(pTemp1, pBuffer, Height * Width * sizeof(BYTE)); BYTE *pTemp2 = new BYTE[Height * Width]; memcpy(pTemp2, pBuffer, Height * Width * sizeof(BYTE)); Template[0] = -1.0; Template[1] = -1.0; Template[2] = -1.0; Template[3] = 0; Template[4] = 0; Template[5] = 0; Template[6] = 1.0; Template[7] = 1.0; Template[8] = 1.0; Edge_Temple(pTemp1,Height,Width,TempH,TempW,TempMX,TempMY,Template,fTempCoef); Template[0] = 1.0; Template[1] = 0; Template[2] = -1.0; Template[3] = 1.0; Template[4] = 0; Template[5] = -1.0; Template[6] = 1.0; Template[7] = 0; Template[8] = -1.0; Edge_Temple(pTemp2,Height,Width,TempH,TempW,TempMX,TempMY,Template,fTempCoef); for (i=0; i pTemp1[Pos(i,j)]) pTemp1[Pos(i,j)] = pTemp2[Pos(i,j)]; } } memcpy(pBuffer, pTemp1, Height*Width*sizeof(BYTE)); delete []pTemp1; delete []pTemp2; }/************************************************************************/ /* 函数：边缘检测——Krisch算子（克瑞斯算子） 说明：调用模板进行卷积运算，取较大值； Krisch算子有8个方向； */ /************************************************************************/ void CDibImage::EdgeKrisch(BYTE *pBuffer, int Height, int Width) { int i,j; int TempH = 3; int TempW = 3; int TempMX = 1; int TempMY = 1; float fTempCoef = 0.5; float Template[9]; BYTE *pTemp1 = new BYTE[Height * Width]; memcpy(pTemp1, pBuffer, Height * Width * sizeof(BYTE)); BYTE *pTemp2 = new BYTE[Height * Width]; memcpy(pTemp2, pBuffer, Height * Width * sizeof(BYTE)); //模板1参数 Template[0] = 5.0; Template[1] = 5.0; Template[2] = 5.0; Template[3] = -3.0; Template[4] = 0; Template[5] = -3.0; Template[6] = -3.0; Template[7] = -3.0; Template[8] = -3.0; Edge_Temple(pTemp1,Height,Width,TempH,TempW,TempMX,TempMY,Template,fTempCoef); //模板2参数 Template[0] = -3.0; Template[1] = 5.0; Template[2] = 5.0; Template[3] = -3.0; Template[4] = 0; Template[5] = 5.0; Template[6] = -3.0; Template[7] = -3.0; Template[8] = -3.0; Edge_Temple(pTemp2,Height,Width,TempH,TempW,TempMX,TempMY,Template,fTempCoef); for (i=0; i pTemp1[Pos(i,j)]) pTemp1[Pos(i,j)] = pTemp2[Pos(i,j)]; } } memcpy(pTemp2,pBuffer,Height*Width*sizeof(BYTE)); //模板3参数 Template[0] = -3.0; Template[1] = -3.0; Template[2] = 5.0; Template[3] = -3.0; Template[4] = 0; Template[5] = 5.0; Template[6] = -3.0; Template[7] = -3.0; Template[8] = 5.0; Edge_Temple(pTemp2,Height,Width,TempH,TempW,TempMX,TempMY,Template,fTempCoef); for (i=0; i pTemp1[Pos(i,j)]) pTemp1[Pos(i,j)] = pTemp2[Pos(i,j)]; } } memcpy(pTemp2,pBuffer,Height*Width*sizeof(BYTE)); //模板4参数 Template[0] = -3.0; Template[1] = -3.0; Template[2] = -3.0; Template[3] = -3.0; Template[4] = 0; Template[5] = 5.0; Template[6] = -3.0; Template[7] = 5.0; Template[8] = 5.0; Edge_Temple(pTemp2,Height,Width,TempH,TempW,TempMX,TempMY,Template,fTempCoef); for (i=0; i pTemp1[Pos(i,j)]) pTemp1[Pos(i,j)] = pTemp2[Pos(i,j)]; } } memcpy(pTemp2,pBuffer,Height*Width*sizeof(BYTE)); //模板5参数 Template[0] = -3.0; Template[1] = -3.0; Template[2] = -3.0; Template[3] = -3.0; Template[4] = 0; Template[5] = -3.0; Template[6] = 5.0; Template[7] = 5.0; Template[8] = 5.0; Edge_Temple(pTemp2,Height,Width,TempH,TempW,TempMX,TempMY,Template,fTempCoef); for (i=0; i pTemp1[Pos(i,j)]) pTemp1[Pos(i,j)] = pTemp2[Pos(i,j)]; } } memcpy(pTemp2,pBuffer,Height*Width*sizeof(BYTE)); //模板6参数 Template[0] = -3.0; Template[1] = -3.0; Template[2] = -3.0; Template[3] = 5.0; Template[4] = 0; Template[5] = -3.0; Template[6] = 5.0; Template[7] = 5.0; Template[8] = -3.0; Edge_Temple(pTemp2,Height,Width,TempH,TempW,TempMX,TempMY,Template,fTempCoef); for (i=0; i pTemp1[Pos(i,j)]) pTemp1[Pos(i,j)] = pTemp2[Pos(i,j)]; } } memcpy(pTemp2,pBuffer,Height*Width*sizeof(BYTE)); //模板7参数 Template[0] = 5.0; Template[1] = -3.0; Template[2] = -3.0; Template[3] = 5.0; Template[4] = 0; Template[5] = -3.0; Template[6] = 5.0; Template[7] = -3.0; Template[8] = -3.0; Edge_Temple(pTemp2,Height,Width,TempH,TempW,TempMX,TempMY,Template,fTempCoef); for (i=0; i pTemp1[Pos(i,j)]) pTemp1[Pos(i,j)] = pTemp2[Pos(i,j)]; } } memcpy(pTemp2,pBuffer,Height*Width*sizeof(BYTE)); //模板8参数 Template[0] = 5.0; Template[1] = 5.0; Template[2] = -3.0; Template[3] = 5.0; Template[4] = 0; Template[5] = -3.0; Template[6] = -3.0; Template[7] = -3.0; Template[8] = -3.0; Edge_Temple(pTemp2,Height,Width,TempH,TempW,TempMX,TempMY,Template,fTempCoef); for (i=0; i pTemp1[Pos(i,j)]) pTemp1[Pos(i,j)] = pTemp2[Pos(i,j)]; } } // memcpy(pBuffer, pTemp1, Height*Width*sizeof(BYTE)); delete []pTemp1; delete []pTemp2; }/************************************************************************/ /* 函数：边缘检测——GaussLaplacian算子（高斯拉普拉斯算子） 说明：Laplacian算子是线形二阶微分算子，具有旋转不变性； 高斯平滑滤波器与Laplacian锐化滤波器结合；先平滑滤波，再边缘检测； */ /************************************************************************/ void CDibImage::EdgeGaussLaplacian(BYTE *pBuffer, int Height, int Width) { int TempH = 5; int TempW = 5; int TempMX = 4; int TempMY = 4; float fTempCoef = 0.25; float Template[25]; BYTE *pTemp1 = new BYTE[Height * Width]; memcpy(pTemp1, pBuffer, Height * Width * sizeof(BYTE)); //设置GuassLaplacian模板参数 Template[0]=-2.0; Template[1]=-4.0; Template[2]=-4.0; Template[3]=-4.0; Template[4]=-2.0; Template[5]=-4.0; Template[6]=0.0; Template[7]=8.0; Template[8]=0.0; Template[9]=-4.0; Template[10]=-4.0; Template[11]=8.0; Template[12]=24.0; Template[13]=8.0; Template[14]=-4.0; Template[15]=-4.0; Template[16]=0.0; Template[17]=8.0; Template[18]=0.0; Template[19]=-4.0; Template[20]=-2.0; Template[21]=-4.0; Template[22]=-4.0; Template[23]=-4.0; Template[24]=-2.0; Edge_Temple(pTemp1,Height,Width,TempH,TempW,TempMX,TempMY,Template,fTempCoef); memcpy(pBuffer, pTemp1, Height*Width*sizeof(BYTE)); delete []pTemp1; }/************************************************************************/ /* 函数：图像分割——阈值分割 说明：灰度值与阈值之差的绝对值小于30，则将阈值赋给图像点； */ /************************************************************************/ void CDibImage::FenGeYuZhi(BYTE *pBuffer, int nYuZhi, int Height, int Width) { int i,j; BYTE *pTemp = new BYTE[Height * Width]; memcpy(pTemp, 0, Height*Width*sizeof(BYTE)); for (i=0; i 200) pBuffer[Pos(i,j)] = 255; else pBuffer[Pos(i,j)] = 0; } } BYTE *pTemp = new BYTE[Height * Width]; memcpy(pTemp, 0, Height*Width*sizeof(BYTE)); for (i=1; i 200) pBuffer[Pos(i,j)] = 255; else pBuffer[Pos(i,j)] = 0; } } BYTE *pTemp = new BYTE[Height*Width*sizeof(BYTE)]; //创建缓冲区，将二值化后的图像数据赋给该缓冲区 memcpy(pTemp,pBuffer,Height*Width*sizeof(BYTE)); bFindStartPoint = false; //先找到最左上方的边界点 for (j = 0; j < Height && !bFindStartPoint; j++) { for(i = 0; i < Width && !bFindStartPoint; i++) { pixel =pTemp[Pos(i,j)]; if(pixel == 255)//如果找到白点 { bFindStartPoint = true; StartPoint.Height = i; StartPoint.Width = j; pTemp[Pos(i,j)] = 255; } } } BeginDirect = 0; //由于起始点是在左下方，故起始扫描沿左上方向 bFindStartPoint = false; //跟踪边界 CurrentPoint.Height = StartPoint.Height; //从初始点开始扫描 CurrentPoint.Width = StartPoint.Width; while(!bFindStartPoint) { bFindPoint = false; while(!bFindPoint) { //沿扫描方向查看一个像素 i = CurrentPoint.Height + Direction[BeginDirect][1]; j = CurrentPoint.Width + Direction[BeginDirect][0]; pixel =pTemp[Pos(i,j)]; if(pixel== 255) { bFindPoint = true; CurrentPoint.Height = CurrentPoint.Height + Direction[BeginDirect][1]; CurrentPoint.Width = CurrentPoint.Width + Direction[BeginDirect][0]; if(CurrentPoint.Height == StartPoint.Height && CurrentPoint.Width == StartPoint.Width) bFindStartPoint = true; i = CurrentPoint.Height; j = CurrentPoint.Width; pTemp[Pos(i,j)] = 255; BeginDirect--; //扫描的方向逆时针旋转两格 if(BeginDirect == -1) BeginDirect = 7; BeginDirect--; if(BeginDirect == -1) BeginDirect = 7; } else { //扫描方向顺时针旋转一格 BeginDirect++; if(BeginDirect == 8) BeginDirect = 0; } } } memcpy(pBuffer, pTemp, Height*Width*sizeof(BYTE)); // 复制图像 delete []pTemp; // 释放内存 }/************************************************************************/ /* 函数：图像测量——图像区域标记； 说明：标记出图像中的连通区域； */ /************************************************************************/ void CDibImage::MeasureBiaoJi(BYTE *pBuffer, int Height, int Width) //对图像区域进行标记 { int i,j; //循环变量 int x_sign=0; int m_temp=0; int x_temp=0; int y_temp=0; int stop=0; int flag[255]; memset(flag,0,255); BYTE *pTemp=new BYTE[Height*Width*sizeof(BYTE)]; //开辟一个临时内存区 memset(pTemp, 255, Height*Width*sizeof(BYTE)); //从左到右标号 for(i=1; i250) { AfxMessageBox("连通区数目太多，请增大阈值！"); stop=1; break; } if(pBuffer[Pos((Height-i-1),j)] == 0)//若当前点为黑点 { if(pBuffer[Pos((Height-i-1+1),j+1)] == 0)//右上 { pTemp[Pos((Height-i-1),j)] = pTemp[Pos((Height-i-1+1),j+1)]; x_temp=pTemp[Pos((Height-i-1+1),j+1)]; flag[x_temp]+=1; //左前 if(pBuffer[Pos((Height-i-1),j-1)] == 0 && pTemp[Pos((Height-i-1),j-1)] != x_temp) { y_temp=pTemp[Pos((Height-i-1),j-1)]; for(int m=1; m<=Height-1; m++) for(int n=1; n<=Width-1; n++) { if(pTemp[Pos((Height-m-1),n)] == y_temp) { flag[y_temp]=0; pTemp[Pos((Height-m-1),n)]=x_temp; flag[x_temp]+=1; } } }//end//左前 //左上 if(pBuffer[Pos((Height-i-1+1),j-1)] == 0 && pTemp[Pos((Height-i-1+1),j-1)] != x_temp) { y_temp=pBuffer[Pos((Height-i-1+1),j-1)]; for(int m=1; m<=Height-1; m++) for(int n=1; n<=Width-1; n++) { if(pTemp[Pos((Height-m-1),n)] == y_temp) { flag[y_temp]=0; pTemp[Pos((Height-m-1),n)]=x_temp; flag[x_temp]+=1; } } }//end//左上 } else if(pBuffer[Pos((Height-i-1+1), j)]==0)//正上 { pTemp[Pos((Height-i-1), j)] = pTemp[Pos((Height-i-1+1), j)]; x_temp = pTemp[Pos((Height-i-1+1), j)]; flag[x_temp]+=1; } else if(pBuffer[Pos((Height-i-1+1), j-1)] == 0)//左上 { pTemp[Pos((Height-i-1), j)]=pTemp[Pos((Height-i-1+1), j-1)]; x_temp = pTemp[Pos((Height-i-1+1), j-1)]; flag[x_temp]+=1; } else if(pBuffer[Pos((Height-i-1), j-1)] == 0)//左前 { pTemp[Pos((Height-i-1), j)]=pTemp[Pos((Height-i-1), j-1)]; x_temp=pTemp[Pos((Height-i-1), j-1)]; flag[x_temp]+=1; } else//没有 { ++x_sign; m_temp=x_sign; pTemp[Pos((Height-i-1), j)] = m_temp; flag[m_temp]=1; } }//end if }// 每列 }//end 每行 }



【图像处理|【图像处理】DibImage图像处理常用算子】


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