opencv倾斜矫正

/****************倾斜校正子程序*****************/
//函数名称：IplImage *Rotate(IplImage *RowImage）
//功能：对每行数字进行倾斜校正
//入口参数：行图像RowImage
//出口参数：旋转后的图像RotateRow
/********************************************/
IplImage *Rotate(IplImage *RowImage)
{
    //建立储存边缘检测结果图像canImage
//     IplImage *canImage=cvCreateImage(CvSize(200,300),IPL_DEPTH_8U,1);
    IplImage *canImage=cvCreateImage(cvGetSize(RowImage),IPL_DEPTH_8U,1);
    //进行边缘检测
    cvCanny(RowImage,canImage,30,200,3);
    //进行hough变换
    CvMemStorage *storage=cvCreateMemStorage();
    CvSeq *lines=NULL;
    lines=cvHoughLines2(canImage,storage,CV_HOUGH_STANDARD,1,CV_PI/180,20,0,0);
    //统计与竖直夹角<30度的直线个数以及其夹角和
    int numLine=0;
    float sumAng=0.0;
    for(int i=0;itotal;i++)
    {
        float *line=(float *)cvGetSeqElem(lines,i);
        float theta=line[1];  //获取角度 为弧度制
        if(theta<30*CV_PI/180 || (CV_PI-theta)<30*CV_PI/180 )
        {
            numLine++;
            sumAng=sumAng+theta;
        }
    }
    //计算出平均倾斜角，anAng为角度制
    float avAng=(sumAng/numLine)*180/CV_PI;
    //获取二维旋转的仿射变换矩阵
    CvPoint2D32f center;
    center.x=float (RowImage->width/2.0);
    center.y=float (RowImage->height/2.0);
    float m[6];
    CvMat M = cvMat( 2, 3, CV_32F, m );
    cv2DRotationMatrix( center,avAng,1, &M);
    //建立输出图像RotateRow
    double a=sin(sumAng/numLine);
    double b=cos(sumAng/numLine);
    int width_rotate=int (RowImage->height*fabs(a)+RowImage->width*fabs(b));
    int height_rotate=int (RowImage->width*fabs(a)+RowImage->height*fabs(b));
    IplImage *RotateRow=cvCreateImage(cvSize(width_rotate,height_rotate),IPL_DEPTH_8U,1);
    //变换图像，并用黑色填充其余值
    m[2]+=(width_rotate-RowImage->width)/2;
    m[5]+=(height_rotate-RowImage->height)/2;
    cvWarpAffine(RowImage,RotateRow, &M,CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS,cvScalarAll(0));
    //释放
    cvReleaseImage(&canImage);
    cvReleaseMemStorage(&storage);
    return RotateRow;
}
int main(int argc, char *argv[])
{
//    QCoreApplication a(argc, argv);
    Mat imgMat = imread("20160802.jpeg");//const String* filename);
// Mat imgMat = imread("DSCN6533.png");//const String* filename);
    if(imgMat.empty())return -1; //是否加载成功
   if(!imgMat.data)return -1;//判断是否有数据
//    IplImage pImg= IplImage(imgMat);
    IplImage *pImg = cvLoadImage("20160802.jpeg");
    IplImage *tImg =Rotate(pImg);
//    IplImage* img = cvCreateImage(cvGetSize(mat),8,1);
//   cvGetImage(matI,img);
   cvSaveImage("rice1.png",tImg);
    //建立储存边缘检测结果图像canImage
    return 0;//a.exec();
}

上述代码会报错：

 Assertion failed (src.type() == dst.type()) in cvWarpAffine, file /home/lbg/softs/opencv-3.0.0/modules/imgproc/src/imgwarp.cpp, line 6369
terminate called after throwing an instance of 'cv::Exception'
  what():  /home/lbg/softs/opencv-3.0.0/modules/imgproc/src/imgwarp.cpp:6369: error: (-215) src.type() == dst.type() in function cvWarpAffine

下面是python的：

__author__ = 'Administrator'

import sys

import numpyas np

import cv2as cv

import math

from argparseimport ArgumentParser

FILENAME= "1.150000001.png";

HOUGH_VOTE= 100

GRAY_THRESH= 150

#srcImgOrg : the source image

#srcImgGray : the source image with gray scale

defcalcRotAngle(srcImgOrg,srcImgGray):

angleD = 0

opWidth = cv.getOptimalDFTSize(srcImgGray.shape[1])

opHeight = cv.getOptimalDFTSize(srcImgGray.shape[0])

padded = cv.copyMakeBorder(srcImgGray, 0, opWidth - srcImgGray.shape[1] , 0, opHeight- srcImgGray.shape[0], cv.BORDER_CONSTANT);

plane = np.zeros(padded.shape,dtype=np.float32)

planes = [padded,plane]

#Merge into a double-channel image

comImg = cv.merge(planes)

cv.dft(comImg,comImg)

cv.split(comImg, planes)

planes[0]= cv.magnitude(planes[0], planes[1]);

magMat = planes[0]

magMat += np.ones(magMat.shape)

cv.log(magMat,magMat);

cx = magMat.shape[1] / 2;

cy = magMat.shape[0] / 2

q0 = magMat[0:cx,0: cy ]

q1 = magMat[cx:,0: cy]

q2 = magMat[0:cx, cy:]

q3 = magMat[cx:,cy:]

c1 = np.vstack((q3,q2))

c2 = np.vstack((q1,q0))

magMat2 = np.hstack((c1,c2))

cv.normalize(magMat2, magMat,0, 1,cv.NORM_MINMAX);

magMat = cv.resize(magMat,(magMat.shape[0] / 2,magMat.shape[1]/2))

magMat = magMat * 255

magMat = cv.threshold(magMat,GRAY_THRESH,255,cv.THRESH_BINARY)[1].astype(np.uint8)

lines = cv.HoughLines(magMat,1,np.pi/180,HOUGH_VOTE);

#cv.imshow("mag_binary", magMat);

#lineImg = np.ones(magMat.shape,dtype=np.uint8)

angle = 0

if lines!= None andlen(lines) != 0:

for linein lines[0]:

#print line

rho = line[0]

theta = line[1]

if (theta< (np.pi/4. ))or (theta > (3.*np.pi/4.0)):

print'Vertical line , rho : %f , theta : %f'%(rho,theta)

pt1 = (int(rho/np.cos(theta)),0)

pt2 = (int((rho-magMat.shape[0]*np.sin(theta))/np.cos(theta)),magMat.shape[0])

#cv.line( lineImg, pt1, pt2, (255))

angle = theta

else:

print'Horiz line , rho : %f , theta : %f'%(rho,theta)

pt1 = (0,int(rho/np.sin(theta)))

pt2 = (magMat.shape[1], int((rho-magMat.shape[1]*np.cos(theta))/np.sin(theta)))

#cv.line(lineImg, pt1, pt2, (255), 1)

angle = theta + np.pi / 2

#cv.imshow('lineImg',lineImg)

#Find the proper angel

if angle> (np.pi / 2):

angle = angle - np.pi

#Calculate the rotation angel

#The image has to be square,

#so that the rotation angel can be calculate right

print'angle : %f'% angle

#print srcImgOrg.shape

alpha = float(srcImgOrg.shape[1])/ float(srcImgOrg.shape[0])

print'alpha : %f'% alpha

if alpha> 1:

angleT = srcImgOrg.shape[1] * np.tan(angle)/ srcImgOrg.shape[0];

angleD = np.arctan(angleT) * 180/ np.pi;

else:

angleD = angle * 180 / np.pi

print'angleD : %f'% angleD

return angleD

defrotImage(srcImgOrg,angleD):

size = srcImgOrg.shape

centerPnt = (srcImgOrg.shape[1] /2,srcImgOrg.shape[0] / 2)

rotMat = cv.getRotationMatrix2D(centerPnt,angleD,scale=1.);

resultImg = cv.warpAffine(srcImgOrg,rotMat,(size[1],size[0]));

#cv.imshow('srcImgOrg',srcImgOrg);

#resultImg = cv.resize(resultImg,(resultImg.shape[0] / 2,resultImg.shape[1]/2))

#cv.imshow("resultImg",resultImg);

fileParts = fileName.split('.')

fileParts[-2]= fileParts[-2]+ '-r'

file= '.'.join(fileParts)

print"file name : %s"% file

ret = cv.imwrite(file,resultImg)

defhandleImage(fileName):

srcImgOrg = cv.imread(fileName)

srcImgGray = cv.imread(fileName,cv.IMREAD_GRAYSCALE).astype(np.float32);

angle = calcRotAngle(srcImgOrg,srcImgGray)

if angle> 0:

rotImage(srcImgOrg,angle)

defmain():

p = ArgumentParser(usage='it is usage tip',description='this is a usage tip')

p.add_argument('--file',default="./",help='input file name')

args = p.parse_args()

#print args.file

handleImage(args.file)

if__name__ == '__main__':

main()

#rotImage(FILENAME)

cv.waitKey( 0)

参考：https://github.com/lyzh1688/SlantCorrection

opencv图像校正（摄像头校正）

需要事先标定：

http://download.csdn.net/download/hs5530hs/9046567

需要事先标定：

http://blog.csdn.net/zht9961020/article/details/7036786