Homological Methods in Feature Extraction of Multidimensional Images

We show that the newly developed homology algorithms are helpful in imaging problems on the example of an algorithm extracting one dimensional features from a noisy image. We indicate that in some situations the global nature of this algorithm may become advantageous when compared with the standard algorithms based on skeletonization and pruning. The algorithm works in every dimension.