【OpenCV】图片几何特征提取

上一版不太好，又重新自己了一遍。

#include<cv.h>  #include<highgui.h>  using namespace cv;using namespace std;CvMemStorage *stroage;IplImage *contourimage;CvSeq *seq = NULL;int ku = -1;double pi = 3.141592;int main(){    stroage = cvCreateMemStorage();    Mat src = imread("E:\\14.jpg");    Mat I;    medianBlur(src, I, 3);    //blur(src, I, Size(3, 3), Point(-1, -1));    //GaussianBlur(src, I, Size(3, 3), 0, 0);    //bilateralFilter(src, I, 5, 0.0, 10.0);    contourimage = cvCreateImage(cvGetSize(&(CvMat)I), 8, 1);    cvtColor(I, I, CV_BGR2GRAY);    Mat contours;    Canny(I, contours, 100, 255);    threshold(contours, contours, 100, 255, CV_THRESH_TRUNC);    int numcontours = cvFindContours(&(CvMat)contours, stroage, &seq, sizeof(CvContour), CV_RETR_LIST);    CvMoments moments;    CvHuMoments hu;    cvMoments(&(CvMat)I, &moments, 0);    cvGetHuMoments(&moments, &hu);    if (ku != numcontours)    {        ku = numcontours;        printf("contournum:::: %d \n", numcontours);    }    CvSeq *c = 0;    int zz = 0;    int totl = 0;    cvSet(contourimage, cvScalar(255, 0, 255));    cvSet(contourimage, cvScalar(125, 0, 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 >= 50 && testdbLength <= 5000)        {            //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);            //cvDrawContours(&(CvMat)contours, c, cvScalar(0, 255, 255), cvScalar(0, 255, 0), 0, 2);            cvRectangle(&(CvMat)contours, cvPoint(testrect.x, testrect.y + testrect.height), cvPoint(testrect.x + testrect.width, testrect.y), cvScalar(255, 0, 255), 1);            double width = testrect.width;            double height = testrect.height;            double juxingmianji = width*height;            //找外界圆            //cvMinEnclosingCircle(c, &center, &radius);             //cout <<  radius << endl;            //cout << center.x << "；" << center.y << endl;            //画外接圆            //cvCircle(&(CvMat)contours, cvPointFrom32f(center), (int)radius, cvScalar(255, 0, 255), 2);            //特征1矩形度            float mianjibi = testdbArea / juxingmianji;            //特征2延长度            float changkuanbi = width / height;            //特征3周长比            float zhouchangbi = 2 * (height + width) / testdbLength;            //特征4似圆度            float r = 4 * pi*testdbArea / (testdbLength*testdbLength);            //特征5形状复杂性            float e = (testdbLength*testdbLength) / testdbArea;            //不动点特征 hu.hu1    hu.hu2            cout << "矩形度：" << mianjibi << endl;            cout << "延长度：" << changkuanbi << endl;            cout << "周长比：" << zhouchangbi << endl;            cout << "似圆度：" << r << endl;            cout << "形状复杂性：" << e << endl;            cout << "一阶矩：" << hu.hu1 << endl;            cout << "二阶矩：" << hu.hu2 << endl;        }    }    namedWindow("Canny");    imshow("Canny", contours);    waitKey();    return 0;}