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【图像算法】彩色图像分割专题三：边缘检测+区域生长法

SkySeraph May 15th 2011 HQU

Email：zgzhaobo@gmail.com QQ：452728574

Latest Modified Date：May 15th 2011 HQU

一原理：

空间转换：RGB转换为HSI http://www.cnblogs.com/skyseraph/archive/2011/05/03/2035643.html，结果见实现图1

边缘检测：在HSI空间，对HSI、H、S、I分别利用Canny进行边缘检测，结果见实现图2

区域生长：首先对边缘检测的图像沿边界进行质心计算，把求的的质心作为种子点；区域生长采用四领域像素聚类。

二源码：

空间转换：http://www.cnblogs.com/skyseraph/archive/2011/05/05/2038317.html

边缘检测：

View Code

  1 //////////////////////////////////////////////////////////////////////////
  2  //                         寻找种子点(边缘检测法)
  3  //////////////////////////////////////////////////////////////////////////
  4  void CColorSegDlg::OnCanny() 
  5  //  Canny边缘检测
  6  {
  7     //  验证
  8      if(!(ToDisplayCtr1))
  9     {
 10         MessageBox("Please Load Pic!");
 11         return;
 12     }
 13     
 14     if(!(ToDisplayCtr2 && ToDisplayCtr3 && ToDisplayCtr4 && ToDisplayCtr5))
 15     {
 16         MessageBox("Please do SpaceConvetion!");
 17         return;
 18     }
 19     
 20     UpdateData(TRUE);
 21     int CANNY_T1,CANNY_T2;    //canny算子双阈值     
 22      CANNY_T1 = m_CannyT1;
 23     CANNY_T2 = m_CannyT2;
 24     
 25     // 边缘检测图像的 "初始化"
 26      ToDisplayCtr2Ed = cvCreateImage(cvGetSize(TheImage),IPL_DEPTH_8U,1);
 27     ToDisplayCtr3Ed = cvCreateImage(cvGetSize(TheImage),IPL_DEPTH_8U,1);
 28     ToDisplayCtr4Ed = cvCreateImage(cvGetSize(TheImage),IPL_DEPTH_8U,1);
 29     ToDisplayCtr5Ed = cvCreateImage(cvGetSize(TheImage),IPL_DEPTH_8U,1);
 30     
 31     //////////对各通道分量
 32      //  定义工作位图并加载
 33      IplImage* a;
 34     a = ToDisplayCtr3;
 35     IplImage* b;
 36     b = ToDisplayCtr4;
 37     IplImage* c;
 38     c = ToDisplayCtr5;
 39     
 40     //  定义辅助位图，描述边缘检测后图像
 41      IplImage* aCanny = cvCreateImage(cvGetSize(a),IPL_DEPTH_8U,1); 
 42     IplImage* bCanny = cvCreateImage(cvGetSize(b),IPL_DEPTH_8U,1); 
 43     IplImage* cCanny = cvCreateImage(cvGetSize(c),IPL_DEPTH_8U,1); 
 44     
 45     //  Canny边缘检测
 46     //cvSobel(a,aCanny,1,0,3);//水平sobel核
 47     cvCanny(a, aCanny, CANNY_T1, CANNY_T2); //阈值选择！
 48     cvCanny(b, bCanny, CANNY_T1, CANNY_T2);
 49     cvCanny(c, cCanny, CANNY_T1, CANNY_T2);
 50     
 51     // 输出并显示
 52     //imageReplace(aCanny,&ToDisplayCtr3); 
 53     //imageReplace(bCanny,&ToDisplayCtr4);
 54     //imageReplace(cCanny,&ToDisplayCtr5);
 55     
 56     cvCopyImage(aCanny,ToDisplayCtr3Ed);// 输出处理结果
 57     cvCopyImage(bCanny,ToDisplayCtr4Ed);
 58     cvCopyImage(cCanny,ToDisplayCtr5Ed);
 59     
 60     DrawPicToHDC(ToDisplayCtr3Ed,IDC_ImgShowCtrl3); //显示
 61     DrawPicToHDC(ToDisplayCtr4Ed,IDC_ImgShowCtrl4);
 62     DrawPicToHDC(ToDisplayCtr5Ed,IDC_ImgShowCtrl5);
 63     
 64     //  释放资源
 65     cvReleaseImage(&aCanny);
 66     cvReleaseImage(&bCanny);
 67     cvReleaseImage(&cCanny);
 68     
 69     
 70     //////////对**空间图像
 71     ///*
 72     //  定义工作位图并加载
 73     IplImage* dstColor;
 74     dstColor = ToDisplayCtr2;
 75     IplImage* dstGray =  cvCreateImage(cvGetSize(dstColor),IPL_DEPTH_8U,1); //cvCanny只接受单通道图像作为输入
 76     cvCvtColor(dstColor,dstGray,CV_RGB2GRAY);
 77     
 78     //  定义辅助位图，描述边缘检测后图像
 79     IplImage* dstCannyGray = cvCreateImage(cvGetSize(dstGray),IPL_DEPTH_8U,1); //cvCanny只接受单通道图像作为输入
 80     
 81     //  Canny边缘检测
 82     cvCanny(dstGray,dstCannyGray,CANNY_T1,CANNY_T2);
 83     
 84     // 输出并显示
 85     cvCopyImage(dstCannyGray,ToDisplayCtr2Ed);
 86     DrawPicToHDC(ToDisplayCtr2Ed,IDC_ImgShowCtrl2);
 87     
 88     cvReleaseImage(&dstGray);
 89     cvReleaseImage(&dstCannyGray);
 90     //*/
 91     
 92 }
 93 
 94 void CColorSegDlg::OnSeedsPoint() 
 95 {
 96     //  验证
 97     if(!(ToDisplayCtr1))
 98     {
 99         MessageBox("Please Load Pic!");
100         return;
101     }
102     
103     if(!(ToDisplayCtr2 && ToDisplayCtr3 && ToDisplayCtr4 && ToDisplayCtr5))
104     {
105         MessageBox("Please do SpaceConvetion!");
106         return;
107     }
108     
109     UpdateData(TRUE);
110     
111     long seedNum=0; //种子点数
112     seed_Header = (seed_Node *)malloc(sizeof(seed_Node));//种子点，链表存贮
113     
114     //  定义工作位图
115     IplImage* src ;
116     IplImage* srcCanny;
117     src = ToDisplayCtr2;
118     
119     if(m_RGB == 0) //R
120     {
121         //src = ToDisplayCtr3;
122         srcCanny = ToDisplayCtr3Ed;
123     }
124     
125     if(m_RGB == 1) //G
126     {
127         //src = ToDisplayCtr4;
128         srcCanny = ToDisplayCtr4Ed;
129     }
130     
131     if(m_RGB == 2) //B
132     {
133         //src = ToDisplayCtr5;
134         srcCanny = ToDisplayCtr5Ed;
135     }
136     
137     if(m_RGB == 3)//RGB
138     {        
139         //src = ToDisplayCtr2;
140         srcCanny = ToDisplayCtr2Ed;
141     }
142     
143     //  验证
144     if(!src && ! srcCanny)
145     {
146         MessageBox("wrong!");
147         return;
148     }
149     
150     //  定义辅助位图
151     IplImage* dst = NULL;
152     IplImage* dstCanny = NULL;
153     
154     dst = cvCreateImage(cvGetSize(src),IPL_DEPTH_8U,3);
155     dstCanny = cvCreateImage(cvGetSize(srcCanny),IPL_DEPTH_8U,1);
156     /*
157     if(m_RGB == 3)
158     {
159     dst = cvCreateImage(cvGetSize(src),IPL_DEPTH_8U,3);
160     dstCanny = cvCreateImage(cvGetSize(srcCanny),IPL_DEPTH_8U,1);
161     }
162     else
163     {
164     dst = cvCreateImage(cvGetSize(src),IPL_DEPTH_8U,1);
165     dstCanny = cvCreateImage(cvGetSize(srcCanny),IPL_DEPTH_8U,1);
166 }*/
167     
168     cvCopyImage(src,dst);
169     cvCopyImage(srcCanny,dstCanny);
170     //dst = src;
171     //dstCanny = srcCanny;
172     
173     //  寻找种子点
174     findSeed(dst,dstCanny,seed_Header,seedNum);
175     
176     //cout<<seedNum<<endl;    
177     m_SeedsPoint = seedNum;    
178     UpdateData(FALSE);
179     
180     cvReleaseImage(&dst);
181     cvReleaseImage(&dstCanny);
182 }
183 
184 //  函数模块
185 //-----------------------------------------------//
186 //功能：寻找区域生长种子点        
187 //参数：dst          转换为**空间(如HSI)的彩色图像
188 //        bundary   寻找的区域：hsi经canny边缘检测后的图像
189 //        seed      种子点，链表存贮
190 //        seedNUM      种子点数
191 //返回：
192 //-----------------------------------------------//
193 void CColorSegDlg::findSeed(IplImage *dst, IplImage *bundary, seed_Node *seed, long &seedNUM) 
194 //  寻找种子点 
195 {
196     int width = bundary->width;
197     int height = bundary->height;
198     bool *flag = (bool *)malloc(sizeof(bool)*width*height);   //像素访问标记
199     bool first = true;
200     
201     memset(flag, 0, sizeof(bool)*width*height);
202     seedNUM = 0;
203     seed_Node *seed_t = seed;
204     
205     for(int row=0; row<height; row++) //列
206         for(int col=0; col<width; col++)
207         {
208             if(((uchar *)(bundary->imageData + 
209                 row*bundary->widthStep))[col*bundary->nChannels] == 0)  //像素值==0
210                 continue;
211             if(flag[row*width+col])  //已经访问过该点
212                 continue;          
213             int X=0, Y=0, num=0;
214             findBundary(bundary, flag, col, row, X, Y, num); //得到区域重心
215             if(first)
216             {
217                 first = false;
218             }
219             else
220             {
221                 seed_t->next = (seed_Node *)malloc(sizeof(seed_Node));
222                 seed_t = seed_t->next;
223             }
224             seed_t->x = X/num;  //增加新种子：质心/重心
225             seed_t->y = Y/num;
226             seed_t->next = NULL;
227             
228             seed_t->I = ((uchar *)(dst->imageData+dst->widthStep*row))[col*dst->nChannels]; //修改！
229             seed_t->J = ((uchar *)(dst->imageData+dst->widthStep*row))[col*dst->nChannels+1];
230             seed_t->K = ((uchar *)(dst->imageData+dst->widthStep*row))[col*dst->nChannels+2];
231             seed_t->seedID = ++seedNUM;           //种子点数加一
232             //segment[bundary->width*seed_t->y + seed_t->x] = seed_t->seedID;
233         }
234         
235         free(flag);
236 }
237 
238 //-----------------------------------------------//
239 //功能：沿边界递归寻找,计算区域重心/质心        
240 //参数：bundary寻找的区域
241 //        flag   像素访问标记
242 //        x/y    区域中的某点
243 //        X/Y       质心/重心
244 //        num       边界连接的像素数
245 //-----------------------------------------------//
246 void CColorSegDlg::findBundary(IplImage *bundary, bool *flag, int x, int y
247                                , int &X, int &Y, int &num) 
248                                //  获取区域重心
249 {
250     if(flag[y*bundary->width+x]) //像素已访问
251         return;
252     if(((uchar *)(bundary->imageData + y*bundary->widthStep))[x*bundary->nChannels] == 0) 
253         return;
254     flag[y*bundary->width+x] = true;    //标记访问
255     X += x;                  //质心X方向累加
256     Y += y;
257     num++;                    //边界连接的像素数加
258     for(int i=-1; i<2; i++)
259         for(int j=-1; j<2; j++) //八点领域扩散
260         {
261             if(!i && !j) continue;
262             if(x+j<0 || x+j>=bundary->width || y+i<0 || y+i>=bundary->height)
263                 continue;
264             findBundary(bundary, flag, x+j, y+i, X, Y, num);//继续寻找
265         }
266 }

区域生长：

//////////////////////////////////////////////////////////////////////////
//						区域生长(基于边缘检测提取种子点)
//////////////////////////////////////////////////////////////////////////
//  区域生长
void CColorSegDlg::OnEdgeRegionGrowth() //消息响应
{
	//  验证
	if(!(ToDisplayCtr1))
	{
		MessageBox("Please Load Pic!");
		return;
	}
	
	if(!(ToDisplayCtr2 && ToDisplayCtr3 && ToDisplayCtr4 && ToDisplayCtr5))
	{
		MessageBox("Please do SpaceConvetion!");
		return;
	}
	
	//  定义工作位图
	IplImage* src ;
	IplImage* srcCanny;
	src = ToDisplayCtr2;
	
	//  判断
	UpdateData(TRUE);
	
	if(m_RGB == 0) //R
	{
		//src = ToDisplayCtr3;
		srcCanny = ToDisplayCtr3Ed;
	}
	
	if(m_RGB == 1) //G
	{
		//src = ToDisplayCtr4;
		srcCanny = ToDisplayCtr4Ed;
	}
	
	if(m_RGB == 2) //B
	{
		//src = ToDisplayCtr5;
		srcCanny = ToDisplayCtr5Ed;
	}
	
	if(m_RGB == 3)//RGB
	{		
		//src = ToDisplayCtr2;
		srcCanny = ToDisplayCtr2Ed;
	}
	
	//  验证
	if(!src && ! srcCanny)
	{
		MessageBox("wrong!");
		return;
	}
	
	//  定义辅助位图
	IplImage* dst = NULL;
	IplImage* dstCanny = NULL;
	
	dst = cvCreateImage(cvGetSize(src),IPL_DEPTH_8U,3);
	dstCanny = cvCreateImage(cvGetSize(srcCanny),IPL_DEPTH_8U,1);
	
	
	cvCopyImage(src,dst);
	cvCopyImage(srcCanny,dstCanny);
	
	//  为分割结果申请空间
	int width = TheImage->width;
	int height = TheImage->height;
	segment = (long *)malloc(sizeof(long)*width*height);    
    memset(segment, 0, sizeof(long)*width*height);
	
	int TT;
	UpdateData(TRUE);
	TT = m_TT;
	
	// 区域生长
    seed_Node *t_Node = seed_Header;
    while(t_Node)                       //基于种子点的区域生长
    {
		regionGrowing(dst, dstCanny, t_Node, t_Node->x, t_Node->y, TT);
		t_Node = t_Node->next;
    }	
	
	//////////分割结果
	
	//  SegResultImg "初始化"
	SegResultImg = cvCreateImage(cvGetSize(TheImage),IPL_DEPTH_8U,3); 
	//  定义工作位图
	IplImage* SegResultsrc;
	SegResultsrc = SegResultImg;
	
	//  定义辅助位图
	IplImage* SegResultdst = cvCreateImage(cvGetSize(SegResultsrc),IPL_DEPTH_8U,3);
	IplImage* SegResultdstRGB = cvCreateImage(cvGetSize(SegResultsrc),IPL_DEPTH_8U,3);
	
	//print_segment(width, height);
    copy_segment(SegResultdst, seed_Header);
	//HSI2RGB(SegResultdst);
	//cvCvtColor(SegResultdst,SegResultdstRGB,CV_HSV2BGR);
	
	cvCopyImage(SegResultdst,SegResultImg);    
	
	//	cvNamedWindow("SegResultdstRGB result");
	// cvShowImage("SegResultdstRGB result", SegResultdstRGB);
	
	cvNamedWindow("SegResultdst result");
    cvShowImage("SegResultdst result", SegResultdst);
	
	//cvSaveImage("res.bmp", SegResultImg);
	
	cvDestroyWindow("segmentation result");	
	
	cvReleaseImage(&dst);
	cvReleaseImage(&dstCanny);
}

//-----------------------------------------------//
uchar CColorSegDlg::color_distance(uchar h1, uchar h2) 
//  计算颜色距离
{
    if(h1<h2)
        return h2 - h1;
    return h1 - h2;
}

//-----------------------------------------------//
//功能：区域生长		
//参数：dst		转换为**空间(如HSI)的彩色图像
//		bundary	区域：HSI经canny边缘检测后的图像
//		seed	链表存贮的种子点
//		xi/yi	种子点坐标
//		T		相似性准则判断 的阈值
//返回：
//-----------------------------------------------//
void CColorSegDlg::regionGrowing(IplImage *dst, IplImage *bundary, seed_Node *seed,  int xi,  int yi, uchar T)
//  区域生长
{
    int sp = 0;  //栈顶指针
    int width = dst->width;
    int height = dst->height;
    //int stuck[100];
    int *stuck = (int *)malloc(sizeof(int)*width*height*2);//分配堆栈空间，存储种子点坐标
    memset(stuck, 0, sizeof(int)*width*height*2);
    stuck[sp++] = xi;
    stuck[sp++] = yi;
    while(sp)
    {
        int y = stuck[--sp];//取出栈顶元素
        int x = stuck[--sp];
        //if(segment[bundary->width*y + x]!=0 )
        //  continue;
		// 
        uchar a1 = ((uchar *)(dst->imageData + y*dst->widthStep))[dst->nChannels*x];
        uchar b1 = ((uchar *)(dst->imageData + y*dst->widthStep))[dst->nChannels*x+1];
        uchar c1 = ((uchar *)(dst->imageData + y*dst->widthStep))[dst->nChannels*x+2];
		// 
        uchar a2 = ((uchar *)(dst->imageData +
			seed->y*dst->widthStep))[dst->nChannels*seed->x];
        uchar b2 = ((uchar *)(dst->imageData +
			seed->y*dst->widthStep))[dst->nChannels*seed->x+1];
        uchar c2 = ((uchar *)(dst->imageData +
			seed->y*dst->widthStep))[dst->nChannels*seed->x+2];
        //  判断两像素是否属于同一区域
		if(color_distance(a1, a2) > T)  
            continue;
        segment[bundary->width*y + x] = seed->seedID;
        //  重新计算区域颜色
		/*seed->I /= 2;       
        seed->I += a1/2;
        seed->J /= 2;
        seed->J += b1/2;
        seed->K /= 2;
        seed->K += c1/2;*/
		seed->I = a2;
		seed->J = b2;
		seed->K = c2;
		
        for(int i=-1; i<2; i++)
            for(int j=-1; j<2; j++) //对四点领域做扩散
            {
                if((i==-1&&j==-1) || (i==-1&&j==1) || (i==1&&j==-1) || (i==1&&j==1))//4领域
                    continue;
                if(i+y<0 || i+y>=dst->height || j+x<0 || j+x>=dst->width)
                    continue;
                if(segment[bundary->width*(y+i) + x + j]!=0 )
                    continue;
                if(((uchar*)(bundary->imageData+bundary->widthStep*(y+i)))[bundary->nChannels*(x+j)] == 255)
                    //到达边界，结束该方向的生长
                    continue;
				
                stuck[sp++] = x+j;//新种子点入栈
                stuck[sp++] = y+i;
                segment[bundary->width*(y+i) + x + j] = -1;
            }
    }
    free(stuck);
	
}

//-----------------------------------------------//	 
void CColorSegDlg::copy_segment(IplImage *pSeg, seed_Node *node)  
//  生成分割图
{
    int width = pSeg->width;
    int height = pSeg->height;
    for(int row=0; row<height; row++)
        for(int col=0; col<width; col++)
        {
            long id = segment[width*row+col];
            seed_Node *t_node = node;
            uchar I, J, K;
            while(t_node)
            {
                if(t_node->seedID == id)   //遍历确定像素所属的区域
                {
                    I = t_node->I;      //分配像素颜色值
                    J = t_node->J;
                    K = t_node->K;
                    break;
                }
                t_node = t_node->next;
            }
            if(!t_node) 
				continue;
            ((uchar *)(pSeg->imageData+row*pSeg->widthStep))[col*pSeg->nChannels] = I;
            ((uchar *)(pSeg->imageData+row*pSeg->widthStep))[col*pSeg->nChannels+1] = J;
            ((uchar *)(pSeg->imageData+row*pSeg->widthStep))[col*pSeg->nChannels+2] = K;
        }
}

void CColorSegDlg::print_segment(int width, int height)
{
	
	
    for(int row=0; row<height; row++)
    {
        for(int col=0; col<width; col++)
        {
            //printf("%ld ", segment[width*row + col]);
			m_Test = segment[width*row + col];
			UpdateData(false);
        }
        //printf("\n");
    }
}
//////////////////////////////////////////////////////////////////////////

三实现：

空间转换

边缘检测

提取种子点后区域生长结果

Author: SKySeraph

Email/GTalk: zgzhaobo@gmail.com QQ：452728574

From： http://www.cnblogs.com/skyseraph/

本文版权归作者和博客园共有，欢迎转载，但未经作者同意必须保留此段声明，且在文章页面明显位置给出原文连接，请尊重作者的劳动成果

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原文地址：https://www.cnblogs.com/skyseraph/p/2047049.html

【图像算法】彩色图像分割专题三：边缘检测+区域生长 法

【图像算法】彩色图像分割专题三：边缘检测+区域生长法