Training a multilayered perceptron to compute the Euler number of a 2-D binary image

Humberto Sossa, Ángel Carreón, Raúl Santiago

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

2 Citas (Scopus)

Resumen

In this short communication, we explain how a Multilayered Perceptron (MLP) can be used to compute the Euler number or Genus of a 2-D binary image. We take as basis the results provided by a mathematical formulation that is known providing exact results in the computation of this important topological image feature to derive two MLP-based architectures, one useful for the 4-connected case and one useful for 8-connected case. We present results with a set of realistic images and compare our proposals in terms of processing with other approaches reported in literature.

Idioma originalInglés
Título de la publicación alojadaPattern Recognition - 8th Mexican Conference, MCPR 2016, Proceedings
EditoresJosé Arturo Olvera-López, José Francisco Martínez-Trinidad, Jesús Ariel Carrasco-Ochoa, Víctor Ayala-Ramírez, Xiaoyi Jiang
EditorialSpringer Verlag
Páginas44-53
Número de páginas10
ISBN (versión impresa)9783319393926
DOI
EstadoPublicada - 2016
Evento8th Mexican Conference on Pattern Recognition, MCPR 2016 - Guanajuato, México
Duración: 22 jun. 201625 jun. 2016

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen9703
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia8th Mexican Conference on Pattern Recognition, MCPR 2016
País/TerritorioMéxico
CiudadGuanajuato
Período22/06/1625/06/16

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