OpenCV图像分割

1、实验概述【实验目的及要求】图像分割【实验原理】 图像分割 【实验环境】Visual C+ 6.0 Xvid实验内容【实验方案设计】 先根据要求查询资料 通过上网查到需要的信息 然后整合做出计划性的步骤   【实验过程】Contour：Houghcircles：Houghlines:3. 源程序Contour：#include "cv.h"#include "highgui.h"int main( int argc, char* argv ) IplImage* src; / 第一条命令行参数确定

2、了图像的文件名。 if( argc = 2 && (src=cvLoadImage(argv1, 0)!= 0) IplImage* dst = cvCreateImage( cvGetSize(src), 8, 3 ); CvMemStorage* storage = cvCreateMemStorage(0); CvSeq* contour = 0; cvThreshold( src, src, 1, 255, CV_THRESH_BINARY ); cvNamedWindow( "Source", 1 ); cvShowImage( "Sou

3、rce", src ); cvFindContours( src, storage, &contour, sizeof(CvContour), CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE ); cvZero( dst ); for( ; contour != 0; contour = contour->h_next ) CvScalar color = CV_RGB( rand()&255, rand()&255, rand()&255 ); /* 用1替代 CV_FILLED 所指示的轮廓外形 */ / cvDr

4、awContours( dst, contour, color, color, -1, CV_FILLED, 8 ); cvDrawContours( dst, contour, color, color, -1, 1, 8 ); cvNamedWindow( "Components", 1 ); cvShowImage( "Components", dst ); cvWaitKey(0); Houghcircles：#include <cv.h>#include <highgui.h>#include <math.h>

5、;int main(int argc, char* argv) IplImage* img; if( argc = 2 && (img=cvLoadImage(argv1, 1)!= 0) IplImage* gray = cvCreateImage( cvGetSize(img), 8, 1 ); CvMemStorage* storage = cvCreateMemStorage(0); cvCvtColor( img, gray, CV_BGR2GRAY ); cvSmooth( gray, gray, CV_GAUSSIAN, 9, 9 ); / smooth it,

6、otherwise a lot of false circles may be detected CvSeq* circles = cvHoughCircles( gray, storage, CV_HOUGH_GRADIENT, 2, gray->height/4, 200, 100 ); int i; for( i = 0; i < circles->total; i+ ) float* p = (float*)cvGetSeqElem( circles, i ); cvCircle( img, cvPoint(cvRound(p0),cvRound(p1), 3, CV

7、_RGB(0,255,0), -1, 8, 0 ); cvCircle( img, cvPoint(cvRound(p0),cvRound(p1), cvRound(p2), CV_RGB(255,0,0), 3, 8, 0 ); cvNamedWindow( "circles", 1 ); cvShowImage( "circles", img ); cvWaitKey(0); return 0;Houghlines:/* 这是一个命令行程序，以图像作为文件输入变量 编译时选择“#if 1”或“#if 0”，可以使用标准和概率HOUGH变换两种方法 *

8、/#include <cv.h>#include <highgui.h>#include <math.h>int main(int argc, char* argv) IplImage* src; if( argc = 2 && (src=cvLoadImage(argv1, 0)!= 0) IplImage* dst = cvCreateImage( cvGetSize(src), 8, 1 ); IplImage* color_dst = cvCreateImage( cvGetSize(src), 8, 3 ); CvMemStorag

9、e* storage = cvCreateMemStorage(0); CvSeq* lines = 0; int i; cvCanny( src, dst, 50, 200, 3 ); cvCvtColor( dst, color_dst, CV_GRAY2BGR );#if 1 lines = cvHoughLines2( dst, storage, CV_HOUGH_STANDARD, 1, CV_PI/180, 150, 0, 0 ); for( i = 0; i < lines->total; i+ ) float* line = (float*)cvGetSeqElem

10、(lines,i); float rho = line0; float theta = line1; CvPoint pt1, pt2; double a = cos(theta), b = sin(theta); if( fabs(a) < 0.001 ) pt1.x = pt2.x = cvRound(rho); pt1.y = 0; pt2.y = color_dst->height; else if( fabs(b) < 0.001 ) pt1.y = pt2.y = cvRound(rho); pt1.x = 0; pt2.x = color_dst->wid

11、th; else pt1.x = 0; pt1.y = cvRound(rho/b); pt2.x = cvRound(rho/a); pt2.y = 0; cvLine( color_dst, pt1, pt2, CV_RGB(255,0,0), 1, 8 ); #else lines = cvHoughLines2( dst, storage, CV_HOUGH_PROBABILISTIC, 1, CV_PI/180, 280, 30, 10 ); for( i = 0; i < lines->total; i+ ) CvPoint* line = (CvPoint*)cvGe

12、tSeqElem(lines,i); cvLine( color_dst, line0, line1, CV_RGB(255,0,0), 1, 8,0 ); #endif cvNamedWindow( "Source", 1 ); cvShowImage( "Source", src ); cvNamedWindow( "Hough", 1 ); cvShowImage( "Hough", color_dst ); cvWaitKey(0); 【结果】1 编写程序Contour：Houghcircles：Hough

13、lines:2 图片Contour：Houghcircles：Houghlines：小结图像分割图像分割是图像处理这门学科中的基础难题,，图像分割是图像处理领域和计算机视觉中的基本而关键的问题。其目的就是将人们感兴趣的目标从图像背景中提取出来，为后续的分类、跟踪、识别、处理等提供基础。由于图像分割的重要性，对图像研究就显得格外重要。指导教师评语及成绩评语：    成绩：           指导教师签名：