Note: This tutorial is a record of teacher Jia Zhigang's opencv course study, and I would like to express my gratitude to teacher Jia.
Requirements: The legal documents scanned by the scanner need to be trimmed to remove the marginal blanks.
For example, the image below, the left is the image to be processed, and the right is the processed image.
Solution: Edge detection ----> Contour detection or straight line detection Maximum circumscribed rectangle---->The area where the largest circumscribed matrix of the screenshot is located
#include <opencv2/opencv.hpp>
#include <iostream>
#include <math.h>
using namespace cv;
using namespace std;
Mat src, gray_src, dst;
int threshold_value = 100;
int max_level = 255;
const char *output_win = "Contours Result";
const char *roi_win = "Final Result";
void FindROI(int, void *);
int main(int argc, char **argv) {
src = imread("/home/fuhong/code/cpp/opencv_learning/src/小案例/imgs/case1.png");
if (src.empty()) {
printf("could not load image...\n");
return -1;
}
namedWindow("input image", CV_WINDOW_AUTOSIZE);
imshow("input image", src);
namedWindow(output_win, CV_WINDOW_AUTOSIZE);
// namedWindow(roi_win, CV_WINDOW_AUTOSIZE);
//createTrackbar("Threshold:", output_win, &threshold_value, max_level, FindROI);
FindROI(0, 0);
waitKey(0);
return 0;
}
void FindROI(int, void *) {
cvtColor(src, gray_src, COLOR_BGR2GRAY); //先将图像转化为灰度图
Mat canny_output;
Canny(gray_src, canny_output, threshold_value, threshold_value * 2, 3, false); //canny边缘检测
vector<vector<Point>> contours;
vector<Vec4i> hireachy;
findContours(canny_output, contours, hireachy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0)); //查找轮廓
/*
* // 在二值图像上发现轮廓使用
cv::findContours(
InputOutputArray binImg, // 输入图像，非0的像素被看成1,0的像素值保持不变，8-bit
OutputArrayOfArrays contours,// 全部发现的轮廓对象
OutputArray, hierachy// 图该的拓扑结构，可选，该轮廓发现算法正是基于图像拓扑结构实现。
int mode, // 轮廓返回的模式
int method,// 发现方法
Point offset=Point()// 轮廓像素的位移，默认（0, 0）没有位移
)
*/
int minw = src.cols * 0.75;
int minh = src.rows * 0.75;
RNG rng(12345);
Mat drawImage = Mat::zeros(src.size(), CV_8UC3);
Rect bbox;
for (size_t t = 0; t < contours.size(); t++) {
//找到轮廓的最小外接斜矩形 参考:https://blog.csdn.net/u013925378/article/details/84563011
RotatedRect minRect = minAreaRect(contours[t]);
float degree = abs(minRect.angle);
// 如果矩阵轮廓大于0.75倍的图像长度和宽度,并且不是图像的最外层轮廓,则是要寻找的轮廓
if (minRect.size.width > minw && minRect.size.height > minh && minRect.size.width < (src.cols - 5)) {
printf("current angle : %f\n", degree);
Point2f pts[4];
minRect.points(pts);
bbox = minRect.boundingRect();
Scalar color = Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255));
for (int i = 0; i < 4; i++) {
line(drawImage, pts[i], pts[(i + 1) % 4], color, 2, 8, 0);
}
}
}
imshow(output_win, drawImage);
if (bbox.width > 0 && bbox.height > 0) {
Mat roiImg = src(bbox);
imshow(roi_win, roiImg);
}
return;
}
effect:
Advanced requirements: Sometimes the image is not positive and has a certain tilt angle. In this case, the image is rotated and the white edges are removed.
Solution: Edge detection----> Contour discovery or straight line detection The largest bounding rectangle---->Calculate the angle to be rotated----->Righten the image----->Edge detection---- > Contour discovery or linear detection of the largest circumscribed rectangle---->Intercept the area where the largest circumscribed matrix is located
Code:
#include <opencv2/opencv.hpp>
#include <iostream>
#include <math.h>
using namespace cv;
using namespace std;
Mat src, gray_src, dst;
int threshold_value = 100;
int max_level = 255;
const char* output_win = "Contours Result";
const char* roi_win = "Final Result";
void FindROI(int, void*);
void Check_Skew(int, void*);
int main(int argc, char** argv) {
src = imread("D:/gloomyfish/case1r.png");
if (src.empty()) {
printf("could not load image...\n");
return -1;
}
namedWindow("input image", CV_WINDOW_AUTOSIZE);
imshow("input image", src);
namedWindow(output_win, CV_WINDOW_AUTOSIZE);
Check_Skew(0, 0);
// namedWindow(roi_win, CV_WINDOW_AUTOSIZE);
//createTrackbar("Threshold:", output_win, &threshold_value, max_level, FindROI);
// FindROI(0, 0);
waitKey(0);
return 0;
}
void Check_Skew(int, void*) {
Mat canny_output;
cvtColor(src, gray_src, COLOR_BGR2GRAY);
Canny(gray_src, canny_output, threshold_value, threshold_value * 2, 3, false);
vector<vector<Point>> contours;
vector<Vec4i> hireachy;
findContours(canny_output, contours, hireachy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0));
Mat drawImg = Mat::zeros(src.size(), CV_8UC3);
float maxw = 0;
float maxh = 0;
double degree = 0;
for (size_t t = 0; t < contours.size(); t++) {
RotatedRect minRect = minAreaRect(contours[t]);
degree = abs(minRect.angle);
if (degree > 0) {
maxw = max(maxw, minRect.size.width);
maxh = max(maxh, minRect.size.height);
}
}
RNG rng(12345);
for (size_t t = 0; t < contours.size(); t++) {
RotatedRect minRect = minAreaRect(contours[t]);
if (maxw == minRect.size.width && maxh == minRect.size.height) {
degree = minRect.angle;
Point2f pts[4];
minRect.points(pts);
Scalar color = Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255));
for (int i = 0; i < 4; i++) {
line(drawImg, pts[i], pts[(i + 1) % 4], color, 2, 8, 0);
}
}
}
printf("max contours width : %f\n", maxw);
printf("max contours height : %f\n", maxh);
printf("max contours angle : %f\n", degree);
imshow(output_win, drawImg);
Point2f center(src.cols / 2, src.rows / 2);
Mat rotm = getRotationMatrix2D(center, degree, 1.0);
Mat dst;
warpAffine(src, dst, rotm, src.size(), INTER_LINEAR, 0, Scalar(255, 255, 255));
imshow("Correct Image", dst);
}
void FindROI(int, void*) {
cvtColor(src, gray_src, COLOR_BGR2GRAY);
Mat canny_output;
Canny(gray_src, canny_output, threshold_value, threshold_value * 2, 3, false);
vector<vector<Point>> contours;
vector<Vec4i> hireachy;
findContours(canny_output, contours, hireachy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0));
int minw = src.cols*0.75;
int minh = src.rows*0.75;
RNG rng(12345);
Mat drawImage = Mat::zeros(src.size(), CV_8UC3);
Rect bbox;
for (size_t t = 0; t < contours.size(); t++) {
RotatedRect minRect = minAreaRect(contours[t]);
float degree = abs(minRect.angle);
if (minRect.size.width > minw && minRect.size.height > minh && minRect.size.width < (src.cols-5)) {
printf("current angle : %f\n", degree);
Point2f pts[4];
minRect.points(pts);
bbox = minRect.boundingRect();
Scalar color = Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255));
for (int i = 0; i < 4; i++) {
line(drawImage, pts[i], pts[(i + 1)%4], color, 2, 8, 0);
}
}
}
imshow(output_win, drawImage);
if (bbox.width > 0 && bbox.height > 0) {
Mat roiImg = src(bbox);
imshow(roi_win, roiImg);
}
return;
}