opencv实践::切边

问题描述

　　真实案例，扫描仪扫描到的法律文件，需要切边，去掉边 缘空白，这样看上去才真实。

#include <opencv2/opencv.hpp>

#include <iostream>

#include <math.h>

using namespace cv;

using namespace std;

#define IMAGE_PATH "D:/case2.png"

Mat src, gray_src, tmp_src, dst;

int threshold_value = ;

int max_level = ;

const char* roi_win = "Final Result";

void FindROI(int, void*);

void Check_Skew(int, void*);

int main(int argc, char** argv) {

    src = imread(IMAGE_PATH);

    if (src.empty()) {

        printf("could not load image...\n");

        return -;

    }

    namedWindow("input image", CV_WINDOW_AUTOSIZE);

    imshow("input image", src);

    //纠正图像角度

    Check_Skew(, );

    //图像切边

    FindROI(, );

    waitKey();

    return ;

}

void Check_Skew(int, void*) {

    //寻找最大轮廓

    Mat canny_output;

    cvtColor(src, gray_src, COLOR_BGR2GRAY);

    //Canny 算法做边缘检测

    Canny(gray_src, canny_output, threshold_value, threshold_value * , , false);

    //在二值图像中寻找轮廓

    vector<vector<Point>> contours;

    vector<Vec4i> hireachy;

    findContours(canny_output, contours, hireachy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(, ));

    //创建一张黑色的图，每个像素的每个通道都为0,Scalar(0,0,0)

    //Mat drawImg = Mat::zeros(src.size(), CV_8UC3);

    float maxw = ;//矩形宽

    float maxh = ;//矩形高

    double degree = ;

    for (size_t t = ; t < contours.size(); t++) {

        RotatedRect minRect = minAreaRect(contours[t]);

        //矩形角度绝对值

        degree = abs(minRect.angle);

        if (degree > ) {

            maxw = max(maxw, minRect.size.width);

            maxh = max(maxh, minRect.size.height);

        }

        if (degree > ) {

            if (maxw == minRect.size.width && maxh == minRect.size.height) {

                degree = minRect.angle;

            }

        }

    }

    printf("max contours width : %f\n", maxw);

    printf("max contours height : %f\n", maxh);

    printf("max contours angle : %f\n\n\n", degree);

    //寻找几何中心

    Point2f center(src.cols / , src.rows / );

    //旋转degree角度

    Mat rotm = getRotationMatrix2D(center, degree, 1.0);

    //对图像做仿射变换

    warpAffine(src, tmp_src, rotm, src.size(), INTER_LINEAR, , Scalar(, , ));

    imshow("Correct Image", tmp_src);

}

void FindROI(int, void*) {

    //灰度图

    cvtColor(tmp_src, gray_src, COLOR_BGR2GRAY);

    Mat canny_output;

    //Canny 算法做边缘检测

    Canny(gray_src, canny_output, threshold_value, threshold_value * , , false);

    //在二值图像中寻找轮廓

    vector<vector<Point>> contours;

    vector<Vec4i> hireachy;

    findContours(canny_output, contours, hireachy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(, ));

    //定义最小轮廓

    float minw = tmp_src.cols*0.5;

    float minh = tmp_src.rows*0.5;

    float minstW = 0.0;

    bool  bfirst = true;

    RotatedRect minstRect;

    Rect bbox;

    for (size_t t = ; t < contours.size(); t++) {

        RotatedRect minRect = minAreaRect(contours[t]);

        if (minRect.size.width > minw && minRect.size.height > minh && minRect.size.width < (src.cols - )) {

            {

                //找宽度最小的矩形，既是要找的图像。

                printf("t = %d, w = %f , h = %f \n",t, minRect.size.width, minRect.size.height);

                if (bfirst)

                {

                    minstW = minRect.size.width;

                    minstRect = minRect;

                    bfirst = false;

                }

                else

                {

                    float tmp = min(minstW, minRect.size.width);

                    if (tmp < minstW)

                    {

                        minstW = tmp;

                        minstRect = minRect;

                    }

                }

            }

        }

    }

    bbox = minstRect.boundingRect();

    if (bbox.width >  && bbox.height > ) {

        Mat roiImg = tmp_src(bbox);

        imshow(roi_win, roiImg);

    }

    return;

}