Thermal Calibration Pattern Detection

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I am looking at creating a calibration pattern that works for both EO and LWIR. As a first step I'm trying to identify crossing heated wires (there are 9 such crossings in the images below) that will overlay a traditional checkerboard. Ideas that come to mind are hough lines and 2D filter maxima, but none seem to give satisfactory results. Any ideas?

#include <string>

#include <opencv2/core.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui.hpp>

void printAbout()
{
  std::cout << "\nLWIR Calibration Pattern Filter Test:"
            << "\n\tThis program... "
            << "\n\t\n\n";
}

int main(int argc, const char** argv)
{
  const cv::String keys =
    "{ @image | <none> | LWIR image calibration target }"
    "{ h help |        | print this message            }";

  cv::CommandLineParser parser(argc, argv, keys);

  if(parser.has("help"))
  {
    printAbout();
    parser.printMessage();
    std::cout << std::endl;
    return 0;
  }

  if(!parser.check())
  {
    parser.printErrors();
    return 0;
  }

  const std::string image = parser.get<std::string>("@image");

  cv::Mat lwir = cv::imread(image, cv::IMREAD_GRAYSCALE);

  cv::Mat kernel = (cv::Mat_<float>(9,9) <<  -8, -8,  0,  1,  4,  1,  0, -8, -8,
                                             -8, -4,  0,  1,  4,  1,  0, -4, -8,
                                              0,  0,  0,  1,  4,  1,  0,  0,  0,
                                              1,  1,  1,  2,  4,  2,  1,  1,  1,
                                              4,  4,  4,  4,  4,  4,  4,  4,  4,
                                              1,  1,  1,  2,  4,  2,  1,  1,  1,
                                              0,  0,  0,  1,  4,  1,  0,  0,  0,
                                             -8, -4,  0,  1,  4,  1,  0, -4, -8,
                                             -8, -8,  0,  1,  4,  1,  0, -8, -8);
  cv::Mat filtered;
  cv::filter2D(lwir, filtered, CV_32F, kernel);

  cv::normalize(filtered, filtered, 1.0, 0.0, cv::NORM_MINMAX, CV_32F);

  cv::imshow("Input", lwir);
  cv::imshow("Filtered", filtered);
  cv::waitKey(0);

  return 0;
}