### Abstract

Original language | English |
---|---|

Pages (from-to) | 19-22 |

Number of pages | 4 |

Journal | Image-A: Applicable Mathematics in Image Engineering |

Volume | 3 |

Issue number | 5 |

Publication status | Published - 15 Mar 2013 |

### Fingerprint

### Bibliographical note

This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 International License### Cite this

*Image-A: Applicable Mathematics in Image Engineering*,

*3*(5), 19-22.

}

*Image-A: Applicable Mathematics in Image Engineering*, vol. 3, no. 5, pp. 19-22.

**Reconstructing persistent graph structures from noisy images.** / Chernov, Alexey; Kurlin, Vitaliy.

Research output: Contribution to journal › Article › Research › peer-review

TY - JOUR

T1 - Reconstructing persistent graph structures from noisy images

AU - Chernov, Alexey

AU - Kurlin, Vitaliy

N1 - This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 International License

PY - 2013/3/15

Y1 - 2013/3/15

N2 - Let a point cloud be a noisy dotted image of a graph on the plane. We present a new fast algorithm for reconstructing the original graph from the given point cloud. Degrees of vertices in the graph are found by methods of persistent topology. Necessary parameters are automatically optimized by machine learning tools.

AB - Let a point cloud be a noisy dotted image of a graph on the plane. We present a new fast algorithm for reconstructing the original graph from the given point cloud. Degrees of vertices in the graph are found by methods of persistent topology. Necessary parameters are automatically optimized by machine learning tools.

M3 - Article

VL - 3

SP - 19

EP - 22

JO - Image-A: Applicable Mathematics in Image Engineering

T2 - Image-A: Applicable Mathematics in Image Engineering

JF - Image-A: Applicable Mathematics in Image Engineering

SN - 1885-4508

IS - 5

ER -