3.3.4 距离变换-扫描
1 //////https://blog.csdn.net/gone_huilin/article/details/53223026
2 #include <opencv2/imgproc/imgproc.hpp>
3 #include <opencv2/core/core.hpp>
4 #include <opencv2/highgui/highgui.hpp>
5 #include <iostream>
6 // 计算欧式距离
7 float calcEuclideanDistance(int x1, int y1, int x2, int y2)
8 {
9 return sqrt(float((x1 - x2)*(x1 - x2) + (y1 - y2)*(y1 - y2)));
10 }
11 // 计算棋盘距离
12 int calcChessboardDistance(int x1, int y1, int x2, int y2)
13 {
14 return cv::max(abs(x1 - x2), abs(y1 - y2));
15 }
16 // 计算街区距离
17 int calcBlockDistance(int x1, int y1, int x2, int y2)
18 {
19 return abs(x1 - x2) + abs(y1 - y2);
20 }
21 // 距离变换函数实现
22 void distanceTrans(cv::Mat &srcImage, cv::Mat &resultIamge)
23 {
24 CV_Assert(srcImage.data != NULL);
25 cv::Mat srcGray, srcBinary;
26 // 转换成灰度图像
27 cv::cvtColor(srcImage, srcGray, CV_RGB2GRAY);
28 // 转换成二值图像
29 threshold(srcGray, srcBinary, 100, 255, cv::THRESH_BINARY);
30 cv::imshow("srcBinary", srcBinary);
31 int rows = srcBinary.rows;
32 int cols = srcBinary.cols;
33 uchar* pDataOne;
34 uchar* pDataTwo;
35 float disPara = 0;
36 float fDisMin = 0;
37 // 第一遍遍历图像用左模板更新像素值
38 for (int i = 1; i < rows - 1; i++)
39 {
40 // 图像指针获取
41 pDataOne = srcBinary.ptr<uchar>(i);
42 for (int j = 1; j < cols; j++)
43 {
44 // 分别计算其左模板掩码相关距离
45 // pL pL
46 // pL p
47 // pL
48 pDataTwo = srcBinary.ptr<uchar>(i - 1);
49 disPara = calcEuclideanDistance(i, j, i - 1, j - 1);
50 fDisMin = cv::min((float)pDataOne[j],
51 disPara + pDataTwo[j - 1]);
52 disPara = calcEuclideanDistance(i, j, i - 1, j);
53 fDisMin = cv::min(fDisMin,
54 disPara + pDataTwo[j]);
55 pDataTwo = srcBinary.ptr<uchar>(i);
56 disPara = calcEuclideanDistance(i, j, i, j - 1);
57 fDisMin = cv::min(fDisMin,
58 disPara + pDataTwo[j - 1]);
59 pDataTwo = srcBinary.ptr<uchar>(i + 1);
60 disPara = calcEuclideanDistance(i, j, i + 1, j - 1);
61 fDisMin = cv::min(fDisMin,
62 disPara + pDataTwo[j - 1]);
63 pDataOne[j] = (uchar)cvRound(fDisMin);
64 }
65 }
66 // 第二遍遍历图像用右模板更新像素值
67 for (int i = rows - 2; i > 0; i--)
68 {
69 pDataOne = srcBinary.ptr<uchar>(i);
70 for (int j = cols - 1; j >= 0; j--)
71 {
72 // 分别计算其右模板掩码相关距离
73 // pR pR
74 // pR p
75 // pR
76 pDataTwo = srcBinary.ptr<uchar>(i + 1);
77 disPara = calcEuclideanDistance(i, j, i + 1, j);
78 fDisMin = cv::min((float)pDataOne[j],
79 disPara + pDataTwo[j]);
80 disPara = calcEuclideanDistance(i, j, i + 1, j + 1);
81 fDisMin = cv::min(fDisMin,
82 disPara + pDataTwo[j + 1]);
83 pDataTwo = srcBinary.ptr<uchar>(i);
84 disPara = calcEuclideanDistance(i, j, i, j + 1);
85 fDisMin = cv::min(fDisMin,
86 disPara + pDataTwo[j + 1]);
87 pDataTwo = srcBinary.ptr<uchar>(i - 1);
88 disPara = calcEuclideanDistance(i, j, i - 1, j + 1);
89 fDisMin = cv::min(fDisMin,
90 disPara + pDataTwo[j + 1]);
91 pDataOne[j] = (uchar)cvRound(fDisMin);
92 }
93 }
94 resultIamge = srcBinary.clone();
95 }
96 int main()
97 {
98 cv::Mat srcImage = cv::imread("D:\\沙漠.jpg");
99 if (!srcImage.data)
100 return -1;
101 cv::Mat resultIamge;
102 distanceTrans(srcImage, resultIamge);
103 cv::imshow("resultIamge", resultIamge);
104 cv::waitKey(0);
105 return 0;
106 }
应用：
https://blog.csdn.net/dan1900/article/details/16989023
https://blog.csdn.net/augusdi/article/details/9022077
https://blog.csdn.net/u014751607/article/details/61919706
https://blog.csdn.net/qq_34784753/article/details/68951918?locationNum=8&fps=1
https://blog.csdn.net/guoruijiushiwo/article/details/72841482
3.3.5 距离变换-distanceTransform
Opencv中distanceTransform方法用于计算图像中每一个非零点距离离自己最近的零点的距离，distanceTransform的第二个Mat矩阵参数dst保存了每一个点与最近的零点的距离信息，图像上越亮的点，代表了离零点的距离越远。
1 ////////https://blog.csdn.net/gone_huilin/article/details/53223066
2 #include <opencv2/imgproc/imgproc.hpp>
3 #include <opencv2/core/core.hpp>
4 #include <opencv2/highgui/highgui.hpp>
5 #include <iostream>
6 int main()
7 {
8 cv::Mat srcImage = cv::imread("D:\\六角星.jpg");
9 if (!srcImage.data)
10 return -1;
11 // 转换为灰度图像
12 cv::Mat srcGray;
13 cvtColor(srcImage, srcGray, CV_BGR2GRAY);
14 // 转换为二值图像
15 cv::Mat srcBinary;
16 threshold(srcGray, srcBinary, 160, 255, cv::THRESH_BINARY);
17 // 距离变换
18 cv::Mat dstImage;
19 cv::distanceTransform(srcBinary, dstImage, CV_DIST_L2,
20 CV_DIST_MASK_PRECISE);
21 // 归一化矩阵
22 cv::normalize(dstImage, dstImage, 0, 1., cv::NORM_MINMAX);
23 cv::imshow("srcBinary", srcBinary);
24 cv::imshow("dstImage", dstImage);
25 cv::waitKey(0);
26 return 0;
27 }
1 #include "core/core.hpp"
2 #include "imgproc/imgproc.hpp"
3 #include "highgui/highgui.hpp"
4
5 using namespace cv;
6
7 int main(int argc, char *argv[])
8 {
9 float maxValue = 0; //定义距离变换矩阵中的最大值
10 //Mat image = imread(argv[1]);
11 Mat image = imread("D:\\字母ABCD.jpg");
12 Mat imageGray;
13 cvtColor(image, imageGray, CV_RGB2GRAY);
14 imageGray = ~imageGray; //取反
15 GaussianBlur(imageGray, imageGray, Size(5, 5), 2); //滤波
16 threshold(imageGray, imageGray, 20, 200, CV_THRESH_BINARY); //阈值
17 imshow("s", imageGray);
18 Mat imageThin(imageGray.size(), CV_32FC1); //定义保存距离变换结果的Mat矩阵
19 distanceTransform(imageGray, imageThin, CV_DIST_L2, 3); //距离变换
20 Mat distShow;
21 distShow = Mat::zeros(imageGray.size(), CV_8UC1); //定义细化后的字符轮廓
22 for (int i = 0; i<imageThin.rows; i++)
23 {
24 for (int j = 0; j<imageThin.cols; j++)
25 {
26 if (imageThin.at<float>(i, j)>maxValue)
27 {
28 maxValue = imageThin.at<float>(i, j); //获取距离变换的极大值
29 }
30 }
31 }
32 for (int i = 0; i<imageThin.rows; i++)
33 {
34 for (int j = 0; j<imageThin.cols; j++)
35 {
36 if (imageThin.at<float>(i, j)>maxValue / 1.9)
37 {
38 distShow.at<uchar>(i, j) = 255; //符合距离大于最大值一定比例条件的点设为255
39 }
40 }
41 }
42 imshow("Source Image", image);
43 imshow("Thin Image", distShow);
44 waitKey();
45 return 0;
46 }
1 ////////distanceTransform应用：查找物体质心
2 ////////https://blog.csdn.net/dcrmg/article/details/52517991
3 #include "core/core.hpp"
4 #include "imgproc/imgproc.hpp"
5 #include "highgui/highgui.hpp"
6
7 using namespace cv;
8
9 int main(int argc, char *argv[])
10 {
11 float maxValue = 0; //定义距离变换矩阵中的最大值
12 Point Pt(0, 0);
13 Mat image = imread("D:\\六角星.jpg");
14 Mat imageGray;
15 cvtColor(image, imageGray, CV_RGB2GRAY);
16 imageGray = ~imageGray; //取反
17 GaussianBlur(imageGray, imageGray, Size(5, 5), 2); //滤波
18 threshold(imageGray, imageGray, 20, 200, CV_THRESH_BINARY); //阈值化
19 Mat imageThin(imageGray.size(), CV_32FC1); //定义保存距离变换结果的Mat矩阵
20 distanceTransform(imageGray, imageThin, CV_DIST_L2, 3); //距离变换
21 Mat distShow;
22 distShow = Mat::zeros(imageGray.size(), CV_8UC1); //定义细化后的字符轮廓
23 for (int i = 0; i<imageThin.rows; i++)
24 {
25 for (int j = 0; j<imageThin.cols; j++)
26 {
27 distShow.at<uchar>(i, j) = imageThin.at<float>(i, j);
28 if (imageThin.at<float>(i, j)>maxValue)
29 {
30 maxValue = imageThin.at<float>(i, j); //获取距离变换的极大值
31 Pt = Point(j, i); //坐标
32 }
33 }
34 }
35 normalize(distShow, distShow, 0, 255, CV_MINMAX); //为了显示清晰，做了0~255归一化
36 circle(image, Pt, maxValue, Scalar(0, 0, 255), 3);
37 circle(image, Pt, 3, Scalar(0, 255, 0), 3);
38 imshow("Source Image", image);
39 imshow("Thin Image", distShow);
40 waitKey();
41 return 0;
42 }
1 ////////https://blog.csdn.net/wuhaibing_cver/article/details/8602461
2 #include <opencv2/imgproc/imgproc.hpp>
3 #include <opencv2/core/core.hpp>
4 #include <opencv2/highgui/highgui.hpp>
5 #include <cv.h>
6 #include <highgui.h>
7
8 int main()
9 {
10 char* filename = "D:\\二值化手.jpg";
11 IplImage* src_image = cvLoadImage(filename, 1);
12 if (!src_image)
13 return -1;
14 cvNamedWindow("src");
15
16 CvSize size = cvGetSize(src_image);
17 IplImage* gray_image = cvCreateImage(size, 8, 1);
18 cvCvtColor(src_image, gray_image, CV_BGR2GRAY);
19
20 IplImage* dist_image = cvCreateImage(size, 32, 1);
21 IplImage* bi_src = cvCreateImage(size, 8, 1);
22 IplImage* dist8u_image = cvCreateImage(size, 8, 1);
23 IplImage* bi_dist = cvCreateImage(size, 8, 1);
24 //原图像二值化
25 cvThreshold(gray_image, bi_src, 100, 255, CV_THRESH_BINARY);
26 //距离变换
27 cvDistTransform(bi_src, dist_image, CV_DIST_L2, 3, 0, 0);
28 //找最大值
29 double max;
30 cvMinMaxLoc(dist_image, 0, &max, 0, 0);
31 cvCvtScale(dist_image, dist8u_image, 255. / max);
32 //对距离图像二值化，去除手指部分
33 cvThreshold(dist8u_image, bi_dist, 80, 255, CV_THRESH_BINARY);
34 //求重心
35 float s = 0.0, x = 0.0, y = 0.0;
36 uchar* data = (uchar*)bi_dist->imageData;
37 int step = bi_dist->widthStep;
38 for (int h = 0; h<bi_dist->height; h++)
39 for (int w = 0; w<bi_dist->width; w++)
40 if (255 == data[step*h + w])
41 {
42 x += w;
43 y += h;
44 s++;
45 }
46 if (s>0)
47 {
48 x = x / s;
49 y = y / s;
50 }
51 CvPoint pos = cvPoint((int)x, (int)y);
52
53 cvCircle(src_image, pos, 3, CV_RGB(255, 0, 0), 1, CV_AA);
54 cvShowImage("src", src_image);
55 cvWaitKey(-1);
56
57 cvDestroyWindow("src");
58 cvReleaseImage(&src_image);
59 cvReleaseImage(&gray_image);
60 cvReleaseImage(&bi_src);
61 cvReleaseImage(&dist8u_image);
62 cvReleaseImage(&bi_dist);
63
64 return 0;
65 }
参考：
https://blog.csdn.net/dcrmg/article/details/52517991
https://blog.csdn.net/wuhaibing_cver/article/details/8602461
原理参考：https://blog.csdn.net/liubing8609/article/details/78483667
其他参考：
https://blog.csdn.net/abcjennifer/article/details/7617883
https://blog.csdn.net/haoji007/article/details/52063389
http://www.linuxkiss.com/287.html
原文地址：https://www.cnblogs.com/thebreakofdawn/p/9484458.html
时间： 2024-10-11 09:33:22