Lattice Identification and Separation: Theory and Algorithm

@article{He2018LatticeIA,
  title={Lattice Identification and Separation: Theory and Algorithm},
  author={Yuchen He and Sung Ha Kang},
  journal={ArXiv},
  year={2018},
  volume={abs/1901.02520}
}
Motivated by lattice mixture identification and grain boundary detection, we present a framework for lattice pattern representation and comparison, and propose an efficient algorithm for lattice separation. We define new scale and shape descriptors, which helps to considerably reduce the size of equivalence classes of lattice bases. These finitely many equivalence relations are fully characterized by modular group theory. We construct the lattice space $\mathscr{L}$ based on the equivalent… 
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