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OpenCV Tutorials —— Template Matching

时间:2014-11-23 17:23:59      阅读:240      评论:0      收藏:0      [点我收藏+]

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模板匹配

从源图像中发掘目标图像

将目标图像块逐像素滑动,然后度量此区域的源图像块和目标图像块的匹配程度

匹配都最高的像素位置作为最终定位

 

void matchTemplate(InputArray image, InputArray templ, OutputArray result, int method)

度量手段 —— 相关性

  1. method=CV_TM_SQDIFF

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  2. method=CV_TM_SQDIFF_NORMED

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  3. method=CV_TM_CCORR

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  4. method=CV_TM_CCORR_NORMED

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  5. method=CV_TM_CCOEFF

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    where

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  6. method=CV_TM_CCOEFF_NORMED

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Code

#include "stdafx.h"

#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>

using namespace std;
using namespace cv;

/// Global Variables
Mat img; Mat templ; Mat result;
char* image_window = "Source Image";
char* result_window = "Result window";

int match_method;
int max_Trackbar = 5;

/// Function Headers
void MatchingMethod( int, void* );

/** @function main */
int main( int argc, char** argv )
{
  /// Load image and template
  img = imread( "dashu.jpg", 1 );
  templ = imread( "temp.jpg", 1 );

  /// Create windows
  namedWindow( image_window, CV_WINDOW_AUTOSIZE );
  namedWindow( result_window, CV_WINDOW_AUTOSIZE );

  /// Create Trackbar
  char* trackbar_label = "Method: \n 0: SQDIFF \n 1: SQDIFF NORMED \n 2: TM CCORR \n 3: TM CCORR NORMED \n 4: TM COEFF \n 5: TM COEFF NORMED";
  createTrackbar( trackbar_label, image_window, &match_method, max_Trackbar, MatchingMethod );	// opencv 没有按钮,拿滑动条将就

  MatchingMethod( 0, 0 );

  waitKey(0);
  return 0;
}

/**
 * @function MatchingMethod
 * @brief Trackbar callback
 */
void MatchingMethod( int, void* )
{
  /// Source image to display
  Mat img_display;
  img.copyTo( img_display );

  /// Create the result matrix
  int result_cols =  img.cols - templ.cols + 1;
  int result_rows = img.rows - templ.rows + 1;

  result.create( result_cols, result_rows, CV_32FC1 );

  /// Do the Matching and Normalize
  matchTemplate( img, templ, result, match_method );
  normalize( result, result, 0, 1, NORM_MINMAX, -1, Mat() );	// 归一化

  /// Localizing the best match with minMaxLoc
  double minVal; double maxVal; Point minLoc; Point maxLoc;
  Point matchLoc;

  minMaxLoc( result, &minVal, &maxVal, &minLoc, &maxLoc, Mat() );	// 返回最小值最大值点位置

  /// For SQDIFF and SQDIFF_NORMED, the best matches are lower values. For all the other methods, the higher the better
  if( match_method  == CV_TM_SQDIFF || match_method == CV_TM_SQDIFF_NORMED )
    { matchLoc = minLoc; }
  else
    { matchLoc = maxLoc; }

  /// Show me what you got
  rectangle( img_display, matchLoc, Point( matchLoc.x + templ.cols , matchLoc.y + templ.rows ), Scalar::all(0), 2, 8, 0 );
  rectangle( result, matchLoc, Point( matchLoc.x + templ.cols , matchLoc.y + templ.rows ), Scalar::all(0), 2, 8, 0 );

  imshow( image_window, img_display );
  imshow( result_window, result );

  return;
}

OpenCV Tutorials —— Template Matching

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原文地址:http://www.cnblogs.com/sprint1989/p/4116762.html

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