Opencv处理图像--细化

秒速五厘米 2022-05-17 05:38 479阅读 0赞

## Opencv处理图像--细化 ##

细化的算法有很多种，但比较常用的算法是查表法

细化是从原来的图中去掉一些点，但仍要保持原来的形状。

实际上是保持原图的骨架。

代码如上：

#include<iostream>
    #include<opencv2/core/core.hpp>
    #include<opencv2/highgui/highgui.hpp>
    
    
    IplImage* ColorSrc ,*ColorSrcCopy;
    
    //#define SHOW
    
    //#define LONG int
    //#define BYTE unsigned char
    /
    //基于索引表的细化细化算法
    //功能：对图象进行细化
    //参数：lpDIBBits：代表图象的一维数组
    //      lWidth：图象高度
    //      lHeight：图象宽度
    //      无返回值
    bool ThiningDIBSkeleton (unsigned char* lpDIBBits, int lWidth, int lHeight)
    {	
    	//循环变量
    	long i;
    	long j;
    	long lLength;
    
    	unsigned char deletemark[256] = {
    		0,0,0,0,0,0,0,1,	0,0,1,1,0,0,1,1,
    		0,0,0,0,0,0,0,0,	0,0,1,1,1,0,1,1,
    		0,0,0,0,0,0,0,0,	1,0,0,0,1,0,1,1,
    		0,0,0,0,0,0,0,0,	1,0,1,1,1,0,1,1,
    		0,0,0,0,0,0,0,0,	0,0,0,0,0,0,0,0,
    		0,0,0,0,0,0,0,0,	0,0,0,0,0,0,0,0,
    		0,0,0,0,0,0,0,0,	1,0,0,0,1,0,1,1,
    		1,0,0,0,0,0,0,0,	1,0,1,1,1,0,1,1,
    		0,0,1,1,0,0,1,1,	0,0,0,1,0,0,1,1,
    		0,0,0,0,0,0,0,0,	0,0,0,1,0,0,1,1,
    		1,1,0,1,0,0,0,1,	0,0,0,0,0,0,0,0,
    		1,1,0,1,0,0,0,1,	1,1,0,0,1,0,0,0,
    		0,1,1,1,0,0,1,1,	0,0,0,1,0,0,1,1,
    		0,0,0,0,0,0,0,0,	0,0,0,0,0,1,1,1,
    		1,1,1,1,0,0,1,1,	1,1,0,0,1,1,0,0,
    		1,1,1,1,0,0,1,1,	1,1,0,0,1,1,0,0
    	};//索引表
    
    	unsigned char p0, p1, p2, p3, p4, p5, p6, p7;
    	unsigned char *pmid, *pmidtemp;
    	unsigned char sum;
    	int changed;
    	bool bStart = true;
    	lLength = lWidth * lHeight;
    	unsigned char *pTemp = (unsigned char *)malloc(sizeof(unsigned char) * lWidth * lHeight);
    	
    	//    P0 P1 P2
    	//    P7    P3
    	//    P6 P5 P4
    
    	while(bStart)
    	{
    		bStart = false;
    		changed = 0;
    
    		//首先求边缘点(并行)
    		pmid = (unsigned char *)lpDIBBits + lWidth + 1;
    		memset(pTemp,  0, lLength);
    		pmidtemp = (unsigned char *)pTemp + lWidth + 1;
    		for(i = 1; i < lHeight -1; i++)
    		{
    			for(j = 1; j < lWidth - 1; j++)
    			{
    				if( *pmid == 0)
    				{
    					pmid++;
    					pmidtemp++;
    					continue;
    				}
    
    				p3 = *(pmid + 1);
    				p2 = *(pmid + 1 - lWidth);
    				p1 = *(pmid - lWidth);
    				p0 = *(pmid - lWidth -1);
    				p7 = *(pmid - 1);
    				p6 = *(pmid + lWidth - 1);
    				p5 = *(pmid + lWidth);
    				p4 = *(pmid + lWidth + 1);
    				
    				sum = p0 & p1 & p2 & p3 & p4 & p5 & p6 & p7;
    				if(sum == 0)
    				{
    					*pmidtemp = 1;
    					
    					#ifdef SHOW
    					cvSet2D(ColorSrc,i,j,cvScalar(0,0,255));
    					#endif
    				}
    
    				pmid++;
    				pmidtemp++;
    			}
    			pmid++;
    			pmid++;
    			pmidtemp++;
    			pmidtemp++;
    		}
    		#ifdef SHOW
    		cvNamedWindow("color");
    		cvShowImage("color",ColorSrc);
    		cvWaitKey(0);
    		#endif
    		
    		//现在开始串行删除
    		pmid = (unsigned char *)lpDIBBits + lWidth + 1;
    		pmidtemp = (unsigned char *)pTemp + lWidth + 1;
    
    		for(i = 1; i < lHeight -1; i++)
    		{
    			for(j = 1; j < lWidth - 1; j++)
    			{
    				if( *pmidtemp == 0)
    				{
    					pmid++;
    					pmidtemp++;
    					continue;
    				}
    
    				p3 = *(pmid + 1);
    				p2 = *(pmid + 1 - lWidth);
    				p1 = *(pmid - lWidth);
    				p0 = *(pmid - lWidth -1);
    				p7 = *(pmid - 1);
    				p6 = *(pmid + lWidth - 1);
    				p5 = *(pmid + lWidth);
    				p4 = *(pmid + lWidth + 1);
    				
    				p1 *= 2;
    				p2 *= 4;
    				p3 *= 8;
    				p4 *= 16;
    				p5 *= 32;
    				p6 *= 64;
    				p7 *= 128;
    
    				sum = p0 | p1 | p2 | p3 | p4 | p5 | p6 | p7;
    			//	sum = p0 + p1 + p2 + p3 + p4 + p5 + p6 + p7;
    				if(deletemark[sum] == 1)
    				{
    					*pmid = 0;
    					bStart = true;
    
    					#ifdef SHOW
    					cvSet2D(ColorSrc,i,j,cvScalar(0,0,0));
    
    					cvNamedWindow("delcolor");
    					cvShowImage("delcolor",ColorSrc);
    					cvWaitKey(2);
    					#endif
    				}
    
    				pmid++;
    				pmidtemp++;
    			}
    
    			pmid++;
    			pmid++;
    			pmidtemp++;
    			pmidtemp++;
    		}
    		
    		#ifdef SHOW
    		printf("过了一圈\n");
    		#endif
    	}
    
    	return true;
    }
    
    int main()
    {
    	//#define WRITERESULT
    	//#define WRITEIMAGE
    
    	IplImage* src = cvLoadImage("char2.png",0); //加载图像并灰度化
    	cvThreshold(src,src,100,255,CV_THRESH_BINARY);  //二值化图像  
    	unsigned char* imagedata ;
    
    	ColorSrc = cvLoadImage("char2.png",1);
    
    	cvNamedWindow("s");
    	cvShowImage("s" , src);
    
    
    	FILE* fp ;
    
    	#ifdef WRITEIMAGE
    		fp = fopen("data255.txt","rt+");
    	#endif
    
    	imagedata = (unsigned char*)malloc(sizeof(char)*src->width*src->height); //动态分配内存
    
    	int x , y;
    	for(y=0;y<src->height;y++)
    	{
    		unsigned char* ptr  = (unsigned char*)(src->imageData + y*src->widthStep);
    		for(x=0;x<src->width;x++)
    		{
    			imagedata[y*src->width+x] = ptr[x] > 0 ? 1 : 0;
    
                #ifdef WRITEIMAGE
    				if(ptr[x] > 0)
    					fprintf(fp,"1");
    				else
    				{
    					fprintf(fp,"0");
    				}
                #endif
    		}
    
    		#ifdef WRITEIMAGE
    			fprintf(fp,"\n");
            #endif
    	}
    
    	#ifdef WRITEIMAGE
    		fclose(fp);
    	#endif
    
    	#ifdef WRITERESULT
    		fp = fopen("result.txt","rt+");
    	#endif
    	
    	ThiningDIBSkeleton(imagedata,src->width,src->height);//进行细化操作
    
    	for(y=0;y<src->height;y++)
    	{
    		unsigned char* ptr  = (unsigned char*)(src->imageData + y*src->widthStep);
    		for(x=0;x<src->width;x++)
    		{
    			ptr[x] = imagedata[y*src->width + x]>0? 255 : 0;
    
    			#ifdef WRITERESULT
    				if(ptr[x] > 0)
    					fprintf(fp,"1");
    				else
    				{
    					fprintf(fp,"0");
    				}
                #endif
    		}
    
    		#ifdef WRITERESULT
    			fprintf(fp,"\n");
            #endif
    	}
    
    	#ifdef WRITERESULT
    		fclose(fp);
    	#endif
    
    	cvNamedWindow("src");
    	cvShowImage("src" , src);
    	cvWaitKey(0);
    
    	cvReleaseImage(&src);
    	cvReleaseImage(&ColorSrc);
    	free(imagedata);
    
    	return 0;
    }

![70][]![70 1][]   细化前后对比

博客参考[https://www.cnblogs.com/zhazhiqiang/p/4487950.html][https_www.cnblogs.com_zhazhiqiang_p_4487950.html]

[70]: https://img-blog.csdn.net/20180807144935990?watermark/2/text/aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3NtMTYxMTE=/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70
[70 1]: /images/20220517/9a9f4dbcc577400fa41b44c78dc28fba.png
[https_www.cnblogs.com_zhazhiqiang_p_4487950.html]: https://www.cnblogs.com/zhazhiqiang/p/4487950.html