A ridge filter will probably give better results. I've tried Mathematica's built in RidgeFilter (which calculates the major eigenvalue of the Hessian matrix at each pixel) on your image:. As you can see, there's only a single peak for every thin dark line. Binarizing and skeletonizing yields: After pruning the skeleton and removing small components (noise) from the image, I get this final.

There are two types auto correlation and cross correlation. correlation is maximum when two signals are similar. correlation is equivalent to multiplying the complex conjugate of frequency spectrum of one signal by the frequency spectrum of the other. In auto correlation same signal is correlated to itself or with shifted version of it.