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法律研究如何使用 OpenCV 在 C++ 中檢測顏色？
我們將瞭解如何檢測特定顏色並根據顏色追蹤物體。顏色檢測和基於顏色檢測的追蹤系統的效能均依賴環境。
如果更改房間光線或更改背景顏色，這將顯著影響顏色檢測。
以下程式演示如何使用 OpenCV 在 C++ 中檢測顏色。
示例
#include<iostream>
#include<opencv2/highgui/highgui.hpp>
#include<opencv2/imgproc/imgproc.hpp>
using namespace std;
using namespace cv;
int main(int argc, char** argv) {
VideoCapture video_load(0);//capturing video from default camera//
namedWindow("Adjust");//declaring window to show the image//
int Hue_Lower_Value = 0;//initial hue value(lower)//
int Hue_Lower_Upper_Value = 22;//initial hue value(upper)//
int Saturation_Lower_Value = 0;//initial saturation(lower)//
int Saturation_Upper_Value = 255;//initial saturation(upper)//
int Value_Lower = 0;//initial value (lower)//
int Value_Upper = 255;//initial saturation(upper)//
createTrackbar("Hue_Lower", "Adjust", &Hue_Lower_Value, 179);//track-bar for lower hue//
createTrackbar("Hue_Upper", "Adjust", &Hue_Lower_Upper_Value, 179);//track-bar for lower-upper hue//
createTrackbar("Sat_Lower", "Adjust", &Saturation_Lower_Value, 255);//track-bar for lower saturation//
createTrackbar("Sat_Upper", "Adjust", &Saturation_Upper_Value, 255);//track-bar for higher saturation//
createTrackbar("Val_Lower", "Adjust", &Value_Lower, 255);//track-bar for lower value//
createTrackbar("Val_Upper", "Adjust", &Value_Upper, 255);//track-bar for upper value//
while (1) {
Mat actual_Image;//matrix to load actual image//
bool temp = video_load.read(actual_Image);//loading actual image to matrix from video stream//
Mat convert_to_HSV;//declaring a matrix to store converted image//
cvtColor(actual_Image, convert_to_HSV, COLOR_BGR2HSV);//converting BGR image to HSV and storing it in convert_to_HSV matrix//
Mat detection_screen;//declaring matrix for window where object will be detected//
inRange(convert_to_HSV,Scalar(Hue_Lower_Value,Saturation_Lower_Value, Value_Lower),Scalar(Hue_Lower_Upper_Value,Saturation_Upper_Value, Value_Upper), detection_screen);//applying track-bar modified value of track-bar//
erode(detection_screen, detection_screen, getStructuringElement(MORPH_ELLIPSE, Size(5, 5)));//morphological opening for removing small objects from foreground//
dilate(detection_screen, detection_screen, getStructuringElement(MORPH_ELLIPSE, Size(5, 5)));//morphological opening for removing small object from foreground//
dilate(detection_screen, detection_screen, getStructuringElement(MORPH_ELLIPSE, Size(5, 5)));//morphological closing for filling up small holes in foreground//
erode(detection_screen, detection_screen, getStructuringElement(MORPH_ELLIPSE, Size(5, 5)));//morphological closing for filling up small holes in foreground//
imshow("Threesholded Image", detection_screen);//showing detected object//
imshow("Original", actual_Image);//showing actual image//
if (waitKey(30) == 27){ //if esc is press break the loop//
break;
}
}
return 0;
}輸出
更新於：2021 年 3 月 10 日
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