基于opencv的颜色识别程序

程序环境：windows10系统

opencv3

vs 2013

步骤：1.手动选点

（分析：由于图像是黑色和绿色的，用红色打点做标记。为了算得矫正的标准尺寸，通过原

坐标点横纵坐标算取平均值）

原始图像上打上红色的点

识别结果显示白色的点

2.利用RGB色域转换为HAV色域得到只有坐标点的图像

其目的是为了算取变换后的标准大小（其值等于横纵点间隔的平均值）1 #include "stdafx.h"

2 #include <stdio.h>

3 //include cv

4 #include "opencv2/highgui/highgui.hpp"

5 #include <opencv2>

6 #include "opencv2/imgproc/imgproc.hpp"

7 #include "opencv2\\features2d\\features2d.hpp"

8 #include "opencv2/calib3d/calib3d.hpp"

9 using namespace cv;

10 using namespace std;

11 #define WINDOW_NAME1 "【原始图窗口】" //为窗口标题定义的宏

12 #define WINDOW_NAME2 "【效果图窗口】" //为窗口标题定义的宏

13 #define WINDOW_NAME3 "【原始变形窗口】" //为窗口标题定义的宏

14 #define WINDOW_NAME4 "【效果变形后图窗口】" //为窗口标题定义的宏

15 #define WINDOW_NAME5 "【截图】" //为窗口标题定义的宏

16 void yuzhi();

17 static int iLowH = 0;

18 static int iHighH = 0;

19

20 static int iLowS = 0;

21 static int iHighS = 0;

22

23 static int iLowV = 0;

24 static int iHighV = 0;

25 int main(){

26

27 cv::namedWindow("Control", WINDOW_NORMAL); //create a window called"Control"

28 cv::createTrackbar("LowH", "Control", &iLowH, 359);

29 cv::createTrackbar("HighH", "Control", &iHighH, 259);

30

31 cv::createTrackbar("LowS", "Control", &iLowS, 255); //Saturation (0 ‐255)

32 cv::createTrackbar("HighS", "Control", &iHighS, 255);

33

34 cv::createTrackbar("LowV", "Control", &iLowV, 255); //Value (0 ‐ 255)

35 cv::createTrackbar("HighV", "Control", &iHighV, 255);//创建3个bar存三个值

36 double scale = 0.5;

37 //cvsize sz;

38 // Cam >> frame;

39 //sz.width = frame.width *0.5;

40 Mat gray,frame;

41 Mat HSVpic;

42 Mat imgThresholded;

43

44 std::vector rgbchannel;

45 std::vector hsvchannel;

46 frame = imread("biaoji2.jpg", 1);

47 imshow("Control", frame);

48 cv::cvtColor(frame, gray, COLOR_BGR2GRAY);

49 cvtColor(frame, HSVpic, COLOR_BGR2HSV);

50

51 split(HSVpic, hsvchannel);

52 //equalizeHist(hsvchannel[2], hsvchannel[2]);

53 merge(hsvchannel, HSVpic);

54

55 //inRange(HSVpic, Scalar(iLowH, iLowS, iLowV), Scalar(iHighH, iHighS,iHighV), imgThresholded); //Threshold the image

56 inRange(HSVpic, Scalar(0, 100, 100), Scalar(40, 250, 250), imgThresholded);//1575168255

57 //‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐//

58 int zhongx = 0;

59 int zhongy = 0;

60 Mat image1 = imgThresholded;

61

62 imshow("hsv", imgThresholded);

63 //sprintf(filename2, "D://pos2//(%d).jpg", i);

64 cv::imwrite("chulihou.jpg", imgThresholded);

65 //on_ContoursChange(0, 0);//回调函数

66

67 waitKey(0);

68 return 0;

69 }

70

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