Training an Artificial Neural Network to Compute the Euler Number of a 2-D Binary Image based on Vertex Chain Codification

Authors

  • Juan Humberto Sossa Azuela Instituto Politécnico Nacional
  • Fernando Arce Centro de Investigaciones en Óptica A.C.
  • Wilfrido Gómez Centro de Investigación y de Estudios Avanzados del IPN
  • Laura Lira Instituto Politécnico Nacional - CIC

DOI:

https://doi.org/10.61467/2007.1558.2022.v13i1.261

Keywords:

Artificial neural network, Euler number, Vertex chain codes, Binary image

Abstract

So-called Vertex Chain Codes have been widely used to describe the shape of the objects. From these codes, several describing features can be obtained, e.g., the Euler characteristic. In this research, we show how Vertex Chain Codes can be used to train an Artificial Neural Network to compute the Euler characteristic of a 2-D binary image. We experimentally demonstrate how a simple linear neuron is enough to attain the goal. We present results with sets of 2-D binary images and objects of different complexity and size

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Published

2021-09-13

How to Cite

Sossa Azuela, J. H., Arce-Vega, F., Gómez-Flores, W., & Lira, L. (2021). Training an Artificial Neural Network to Compute the Euler Number of a 2-D Binary Image based on Vertex Chain Codification. International Journal of Combinatorial Optimization Problems and Informatics, 13(1), 4–17. https://doi.org/10.61467/2007.1558.2022.v13i1.261

Issue

Vol. 13 No. 1 (2022)

Section

Articles

License

Copyright (c) 2022 International Journal of Combinatorial Optimization Problems and Informatics

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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