### Abstract

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

Pages (from-to) | 29-36 |

Number of pages | 8 |

Journal | УНИВЕРСИТЕТСКИЙ НАУЧНЫЙ ЖУРНАЛ |

Issue number | 22 |

Publication status | Published - 2016 |

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### Scopus subject areas

- Computer Science(all)

### Cite this

*УНИВЕРСИТЕТСКИЙ НАУЧНЫЙ ЖУРНАЛ*, (22), 29-36.

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*УНИВЕРСИТЕТСКИЙ НАУЧНЫЙ ЖУРНАЛ*, no. 22, pp. 29-36.

**On the method of digital image analysis based on the construction of a stationary flow on graph.** / Соловьев, Игорь Павлович; Ампилова, Наталья Борисовна; Сергеев, Владислав Дмитриевич.

Research output

TY - JOUR

T1 - On the method of digital image analysis based on the construction of a stationary flow on graph

AU - Соловьев, Игорь Павлович

AU - Ампилова, Наталья Борисовна

AU - Сергеев, Владислав Дмитриевич

PY - 2016

Y1 - 2016

N2 - We describe a method for digital image analysis, which is based on the representation of an image by the oriented graph. Vertices correspond to image pixels, edges connect nearest neighbors. We assign a measure to all edges so that to obtain Markov chain on the graph. In accordance with the initial measure distribution the stationary flow is constructed and weighted entropy is calculated. The algorithm is implemented both for the base case (vertex corresponds to one pixel) and the optimized one –- vertex corresponds to a cell of the image partition. The choice of the maximum allowed cell size depends on the image structure and may be obtained experimentally – comparing the weighted entropy values and run times for base and optimized variants. The results of calculations for some classes of biomedical preparations images are given. The described optimization reduces run time in 3-4 times.

AB - We describe a method for digital image analysis, which is based on the representation of an image by the oriented graph. Vertices correspond to image pixels, edges connect nearest neighbors. We assign a measure to all edges so that to obtain Markov chain on the graph. In accordance with the initial measure distribution the stationary flow is constructed and weighted entropy is calculated. The algorithm is implemented both for the base case (vertex corresponds to one pixel) and the optimized one –- vertex corresponds to a cell of the image partition. The choice of the maximum allowed cell size depends on the image structure and may be obtained experimentally – comparing the weighted entropy values and run times for base and optimized variants. The results of calculations for some classes of biomedical preparations images are given. The described optimization reduces run time in 3-4 times.

M3 - Article

SP - 29

EP - 36

JO - УНИВЕРСИТЕТСКИЙ НАУЧНЫЙ ЖУРНАЛ

JF - УНИВЕРСИТЕТСКИЙ НАУЧНЫЙ ЖУРНАЛ

SN - 2222-5064

IS - 22

ER -