利用opencv进行颜色识别（基于opencv的颜色识别程序）
利用opencv进行颜色识别（基于opencv的颜色识别程序）2.利用RGB色域转换为HAV色域得到只有坐标点的图像识别结果显示白色的点（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
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/core/core.hpp>
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<Mat> rgbchannel;
45 std::vector<Mat> 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
