【图像识别】图像特征提取备忘

提取的是一阶不变距，二阶不变距，外接矩形面积比，外接矩形长宽比，紧凑度五个特征值。 留自己备忘。还不知道可不可以做到识别。

#include <cv.h> #include <highgui.h> #include <stdio.h> #include <iostream> #include <fstream> using namespace std; char* filename = "D:\\数据集\\数据集\\1.png"; int ithreshold = 0; IplImage *Image1, *Image2; CvMemStorage *stroage; IplImage *contourimage; CvSeq *seq = NULL; int ivalue = 0; int ku = -1; void changebar(int) { ithreshold = ivalue; cvThreshold(Image1, Image2, 150, 255, CV_THRESH_TRUNC); int numcontours = cvFindContours(Image2, stroage, &seq, sizeof(CvContour), CV_RETR_LIST); CvMoments moments; CvHuMoments hu; cvMoments(Image2, &moments, 0); cvGetHuMoments(&moments, &hu); cout << hu.hu1 << "/" << hu.hu2 << "/" << hu.hu3 << "/" << hu.hu4 << "/" << hu.hu5 << "/" << hu.hu6 << "/" << hu.hu7 << "/" << "/" << endl; if (ku != numcontours) { ku = numcontours; printf("contournum:::: %d \n", numcontours); } CvSeq *c = 0; int zz = 0; int totl = 0; cvSet(contourimage, cvScalar(255, 255, 255)); cvSet(contourimage, cvScalar(125, 125, 125)); CvPoint2D32f center; float radius; CvPoint2D32f rectpoint[4]; CvContour *testcontour = 0; //c为轮廓顶点数组 for (c = seq; c != NULL; c = c->h_next) { // 取得轮廓面积 double testdbArea = fabs(cvContourArea(c, CV_WHOLE_SEQ)); //取得轮廓长度 double testdbLength = cvArcLength(c); c->block_max; if (testdbArea >= 1000 && testdbLength <= 1000) { //点集的最外面（up-right）矩形边界 CvRect testrect = cvBoundingRect(c); //轮廓最小外界矩形 CvBox2D testbox = cvMinAreaRect2(c); //在图像上绘制外部和内部轮廓 cvDrawContours(contourimage, c, cvScalar(0, 0, 255), cvScalar(0, 0, 0), 0, 2); //通过对角线上的两个顶点绘制简单、指定粗细或者带填充的矩形 cvRectangle(contourimage, cvPoint(testrect.x, testrect.y + testrect.height), cvPoint(testrect.x + testrect.width, testrect.y), cvScalar(0, 0, 0), 2); //计算面积 double sq = testrect.width*testrect.height; double bili = (double)testrect.height/testrect.width; //找外界圆 cvMinEnclosingCircle(c, &center, &radius); //画外接圆 cvCircle(contourimage, cvPointFrom32f(center), (int)radius, cvScalar(0, 0, 0), 2); //计算输入的二维盒子顶点 cvBoxPoints(testbox, rectpoint); //cvRectangle(contourimage, cvPoint(testrect.x, testrect.y + testrect.height), cvPoint(testrect.x + testrect.width, testrect.y), cvScalar(0, 0, 0), 2); for (int i = 0; i<4; i++) { //cvLine(contourimage, cvPointFrom32f(rectpoint[i]), cvPointFrom32f(rectpoint[(i + 1) % 4]), CV_RGB(0, 0, 255), 2); } cvShowImage("grotto", contourimage); totl++; printf("contournum:::: %d 轮廓面积:::: %f 轮廓长度:::: %f 和外接矩形面积比例::::%f 外接矩形长宽比:::%f \n", zz, testdbArea, testdbLength, testdbArea/sq,bili); float jincou = testdbArea / (testdbLength*testdbLength); printf("紧凑度：%f\n", jincou); ofstream myfile("C:/Users/s/Desktop/get.txt", ios::out); myfile << hu.hu1 << "," << hu.hu2 << "," << testdbArea / sq << "," << bili <<","<<jincou<< endl; cvWaitKey(0); } zz++; // cvWaitKey(0); } printf("totl:::: %d \n", totl); cvSaveImage("zzzz.jpg", contourimage); }; int main() { Image1 = cvLoadImage(filename, 0); Image2 = cvCreateImage(cvGetSize(Image1), 8, 1); cvNamedWindow("grotto", 1); contourimage = cvCreateImage(cvGetSize(Image1), 8, 3); stroage = cvCreateMemStorage(); ivalue = 1; changebar(10); int iexit = 0; while (iexit != 32) { iexit = cvWaitKey(0); } cvDestroyWindow("grotto"); exit(1); return 0; }