LogPolarFFTTemplateMatcher
This project is an opencv implementation of rotation and scale invariant Log-Polar FFT template matcher.
Dependencies:
- opencv mandatory.
- gtest if you want build test.
Appended canny preprocessing, results become more robust. You can change its parameters in LogPolarFFTTemplateMatch method.
Usage example:
#include "fftm.hpp"
using namespace std;
using namespace cv;
//-----------------------------------------------------------------------------------------------------
//
//-----------------------------------------------------------------------------------------------------
int main(int argc, unsigned int** argv)
{
Mat im0 = imread("cat.png", 1);
Mat im1 = imread("cat_part.png", 1);
imshow("im1", im1);
imshow("im0", im0);
// As input we need equal sized images, with the same aspect ratio,
// scale difference should not exceed 1.8 times.
RotatedRect rr = LogPolarFFTTemplateMatch(im0, im1,200,100);
// Plot rotated rectangle, to check result correctness
Point2f rect_points[4];
rr.points(rect_points);
for (int j = 0; j < 4; j++)
{
line(im0, rect_points[j], rect_points[(j + 1) % 4], Scalar(255, 0, 0), 2, CV_AA);
}
imshow("result", im0);
waitKey();
}Program will show result as below:
References
(1) An FFT-based technique for translation, rotation and scale-invariant image registration. BS Reddy, BN Chatterji. IEEE Transactions on Image Processing, 5, 1266-1271, 1996
(2) An IDL/ENVI implementation of the FFT-based algorithm for automatic image registration. H Xiea, N Hicksa, GR Kellera, H Huangb, V Kreinovich. Computers & Geosciences, 29, 1045-1055, 2003.
(3) Image Registration Using Adaptive Polar Transform. R Matungka, YF Zheng, RL Ewing. IEEE Transactions on Image Processing, 18(10), 2009.
Based on python version of algorithm: http://www.lfd.uci.edu/~gohlke/code/imreg.py.html