Learning an Artificial Neural Network to Discover Combinations of Bit-Quads to Compute the Euler Characteristic of a 2-D Binary Image

Authors

  • Fernando Arce Vega Centro de Investigaciones en Óptica, A. C.
  • Juan Humberto Sossa Azuela Instituto Politécnico Nacional, Centro de Investigación en Computación
  • Wilfrido Gómez Flores Centro de Investigación y de Estudios Avanzados
  • Laura Georgina Lira Vargas Instituto Politécnico Nacional, Centro de Investigación en Computación

DOI:

https://doi.org/10.13053/cys-26-1-4021

Keywords:

Euler characteristic, bit-quads, holes, objects, artificial neural network

Abstract

The Image Analysis community has widely used so-called bit-quads to propose formulations for computing the Euler characteristic of a 2-D binary image. Reported works have manually proposed different combinations of bit-quads to provide one or more formulations to calculate this important topological feature. This paper empirically shows how an Artificial Neural Network can be trained to find an optimal combination of bit-quads to compute the Euler characteristic of any binary image. We present results with binary images of different complexities and sizes and compare them with state-of-the-art machine learning algorithms.

Downloads

Published

2022-03-26

Issue

Vol. 26 No. 1 (2022): Recent Advances in Language & Knowledge Engineering (Guest editors: D. Pinto, B. Beltrán, A. Vázquez, D. Vilariño)

Section

Articles

License 

Hereby I transfer exclusively to the Journal "Computación y 
Sistemas", published by the Computing Research Center (CIC-IPN),
the Copyright of the aforementioned paper. I also accept that these 
rights will not be transferred to any other publication, in any other 
format, language or other existing means of developing.
I certify that the paper has not been previously disclosed or simultaneo
usly submitted to any other publication, and that it does not contain 
material whose publication would violate the Copyright or other 
proprietary rights of any person, company or institution. I certify that 
I have the permission from the institution or company where I work or 
study to publish this work.
The representative author accepts the responsibility for the publication
of this paper on behalf of each and every one of the authors. 
This transfer is subject to the following conditions:
  • The authors retain all ownership rights (such as patent rights) of this work, except for the publishing rights transferred to the CIC, through this document.
  • Authors retain the right to publish the work in whole or in part in any book they are the authors or publishers. They can also make use of this work in conferences, courses, personal web pages, and so on.
  • Authors may include working as part of his thesis, for non-profit distribution only.