opencv3/C++ 直方圖反向投影實例

2020-01-26 13:22:33

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直方圖反向投影：

即取直方圖中的值，按直方圖面積由大到小，對其對應的像素也由大到小賦予新值。即某種灰度值在圖像中所占面積越大，其對應的像素的新值就越大；反之就越小。

void calcBackProject( const Mat* images, //源數組/圖像；有相同的大小和深度(CV_8U或CV_32F)。int nimages,//源圖像的數量const int* channels, //計算反投影的通道列表；通道數量必須與直方圖維度相匹配。InputArray hist,//輸入直方圖。OutputArray backProject, //目標反向投影數組，與images[0]大小、深度相同的單通道數組。const float** ranges,//每個維度的直方圖bin邊界數組。double scale = 1, //輸出反向投影的可選比例因子。bool uniform = true //直方圖是否均勻的標志。);

示例：

獲取測試圖像中每個像素的hue數據 hi,j，并找到 hi,j 在hue直方圖中的bin的位置

#include<opencv2/opencv.hpp>using namespace cv;Mat hue;int bins = 10;void histBackprojection(int, void*);int main(){ Mat src, hsv; src = imread("E:/image/image/shape.jpg"); if (src.empty()) {  printf("can not load image /n");  return -1; } namedWindow("input", WINDOW_AUTOSIZE);  imshow("input", src); cvtColor(src, hsv, COLOR_BGR2HSV);  hue.create(hsv.size(), hsv.depth()); int ch[] = {0, 0}; //分離Hue通道:色相通道 mixChannels(&hsv, 1, &hue, 1, ch, 1); //創建Trackbar來輸入bin的數目 createTrackbar("bins:", "input", &bins, 255, histBackprojection); histBackprojection(0, 0); waitKey(0); return 0;}void histBackprojection(int, void*){ MatND hist, backproj; int histSize = max(bins, 2); float range[] = {0, 255}; const float *ranges = {range}; //計算直方圖 calcHist(&hue, 1, 0, Mat(), hist,1, &histSize, &ranges, true, false); //將直方圖bin的數值歸一化到0-255 normalize(hist, hist, 0, 255, NORM_MINMAX, -1, Mat()); //計算反向投影 calcBackProject(&hue, 1, 0, hist, backproj, &ranges, 1, true); namedWindow("backprogection", WINDOW_AUTOSIZE); imshow("backprogection", backproj); //顯示直方圖 int binsW = cvRound((double)500/histSize); Mat histImg = Mat::zeros(500, 500, CV_8UC3); RNG rng(123); for (int i = 0; i < bins; i++) {  Scalar color = Scalar(rng.uniform(0,255),rng.uniform(0,255),rng.uniform(0,255));  rectangle(histImg, Point(i*binsW, 500), Point((i+1)*binsW, 500 - cvRound(hist.at<float>(i) * 500 / 255.0)), color, -1); } namedWindow("histogram", WINDOW_AUTOSIZE); imshow("histogram", histImg);}