opencv31联通阈分析

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此程序为opencv自带例程

#include <opencv2/core/utility.hpp>#include "opencv2/imgproc.hpp"#include "opencv2/imgcodecs.hpp"#include "opencv2/highgui.hpp"#include <iostream>using namespace cv;using namespace std;Mat img;int threshval = 100;static void on_trackbar(int, void*){Mat bw = threshval < 128 ? (img < threshval) : (img > threshval);Mat labelImage(img.size(), CV_32S);int nLabels = connectedComponents(bw, labelImage, 8);std::vector<Vec3b> colors(nLabels);colors[0] = Vec3b(0, 0, 0);//backgroundfor (int label = 1; label < nLabels; ++label) {colors[label] = Vec3b((rand() & 255), (rand() & 255), (rand() & 255));}Mat dst(img.size(), CV_8UC3);for (int r = 0; r < dst.rows; ++r) {for (int c = 0; c < dst.cols; ++c) {int label = labelImage.at<int>(r, c);Vec3b &pixel = dst.at<Vec3b>(r, c);pixel = colors[label];}}imshow("Connected Components", dst);}static void help(){cout << "\n This program demonstrates connected components and use of the trackbar\n""Usage: \n""  ./connected_components <image(../data/stuff.jpg as default)>\n""The image is converted to grayscale and displayed, another image has a trackbar\n""that controls thresholding and thereby the extracted contours which are drawn in color\n";}const char* keys ={"{help h||}{@image|../data/stuff.jpg|image for converting to a grayscale}"};int main(int argc, const char** argv){CommandLineParser parser(argc, argv, keys);if (parser.has("help")){help();return 0;}string inputImage = parser.get<string>(0);//img = imread(inputImage.c_str(), 0);img = imread("G:\\opencv31\\opencv\\sources\\samples\\data\\pic1.png", 0);if (img.empty()){cout << "Could not read input image file: " << inputImage << endl;return -1;}namedWindow("Image", 1);imshow("Image", img);namedWindow("Connected Components", 1);createTrackbar("Threshold", "Connected Components", &threshval, 255, on_trackbar);on_trackbar(threshval, 0);waitKey(0);return 0;}

效果如下。代码慢慢看吧。

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