使用OpenCV库快速求解相机内参

113 阅读 0 评论 75 点赞

我是靠谱客的博主大胆月光，这篇文章主要介绍使用OpenCV库快速求解相机内参，现在分享给大家，希望可以做个参考。

本文主要介绍如何使用OpenCV库函数求解相机内参。具体可查阅官网：https://docs.opencv.org/master/dc/dbb/tutorial_py_calibration.html。
关于相机内参的求解还有很多其它的工具，如使用MATLAB求解会更方便，直接调用MATLAB中的APP即可。

1.背景知识

关于相机标定的详细理论可以参考博客：《深入理解张正友相机标定法：数学理论详细推导》。
相机内参形式如下，是一个 $3 \times 3$ 的矩阵，其中 $f_x,f_y)$ 是相机焦距， $c_x,c_y)$ 是光学中心。相机内参对于相机而言是唯一的，因此只要计算出了相机内参，就可以在同一相机拍摄的其它图像上重复使用。
$f_x & 0 & c_x \ 0 & f_y & c_y \ 0 & 0 & 1 end{matrix} right] tag{1}$

2.OpenCV库求相机内参

这里使用官方提供的图片来演示如何求解相机内参，目前已有某一相机拍摄的棋盘格图片若干张（20-30张不等），部分图片如下：

image1	image2

使用`OpenCV`库求解相机内参代码如下，其中`mtx`为相机内参, `dist`为畸变系数，

复制代码

import numpy as np
import cv2
import glob

# extract object points and image points
objp = np.zeros((6*8, 3), np.float32)
objp[:, :2] = np.mgrid[0:8, 0:6].T.reshape(-1, 2)

# Arrays to store object points and image points from all the images.
objpoints = []   
imgpoints = []

images = glob.glob('calibration_wide/GO*.jpg')

# Step through the list and search for chessboard corners
for idx, fname in enumerate(images):
    img = cv2.imread(fname)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# Find the chessboard corners
    ret, corners = cv2.findChessboardCorners(gray, (8, 6), None)    
    if ret == True:
        objpoints.append(objp)
        imgpoints.append(corners)

# Draw and display the corners
        cv2.drawChessboardCorners(img, (8, 6), corners, ret)
        cv2.imshow('img', img)
        cv2.waitKey(500)

# calibrate
img = cv2.imread('test_image.jpg')
img_size = (img.shape[1], img.shape[0])

# Do camera calibration given objects points and image points
ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, img_size, None, None)

dst = cv2.undistort(img, mtx, dist, None, mtx)   
cv2.imwrite('test_undist.jpg', dst)

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
import numpy as np
import cv2
import glob

# extract object points and image points
objp = np.zeros((6*8, 3), np.float32)
objp[:, :2] = np.mgrid[0:8, 0:6].T.reshape(-1, 2)

# Arrays to store object points and image points from all the images.
objpoints = []   
imgpoints = []   

images = glob.glob('calibration_wide/GO*.jpg')

# Step through the list and search for chessboard corners
for idx, fname in enumerate(images):
    img = cv2.imread(fname)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    # Find the chessboard corners
    ret, corners = cv2.findChessboardCorners(gray, (8, 6), None)    
    if ret == True:
        objpoints.append(objp)
        imgpoints.append(corners)

        # Draw and display the corners
        cv2.drawChessboardCorners(img, (8, 6), corners, ret)
        cv2.imshow('img', img)
        cv2.waitKey(500)

# calibrate
img = cv2.imread('test_image.jpg')
img_size = (img.shape[1], img.shape[0])

# Do camera calibration given objects points and image points
ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, img_size, None, None)

dst = cv2.undistort(img, mtx, dist, None, mtx)   
cv2.imwrite('test_undist.jpg', dst)