Análisis de Métodos de Medición de Complejidad de Imagen - Image Complexity Measurement Methods: A Survey

Authors

  • Luis Madrid Herrera Instituto Tecnológico de Chihuahua
  • Mario Ignacio Chacón Murguía Instituto Tecnológico de Chihuahua
  • Juan Alberto Ramírez Quintana Instituto Tecnológico de Chihuahua

DOI:

https://doi.org/10.32870/recibe.v7i2.99

Keywords:

Image Complexity, Visual Complexity, Image Complexity Applications, Eye Tracking, EEG, MEG

Abstract

La complejidad de imágenes ha sido estudiada con la finalidad proponer algoritmos computacionales que puedan estimarla simulando el criterio humano, para su aplicación en diversas áreas de procesamiento de imágenes. En este artículo se presenta un estudio de los métodos para determinar la complejidad de imágenes publicados recientemente, se realiza una clasificación basada en las características utilizadas para determinar la complejidad de una imagen y se describen brevemente. En total se analizaron 28 artículos desde el año 2005 a la actualidad, donde se encontraron 34 métodos, los cuales están basados en enfoques computacionales y enfoques humanos. Las categorías en las que se clasifican son: información de bordes, información del color y/o intensidad, grado de compresión, combinado, criterio humano y reacción humana. También, se dan a conocer las bases de datos utilizadas para evaluar los métodos de medición. Por último, se realiza un análisis de la cantidad de métodos que se encuentran en cada categoría, características más utilizadas, cantidad de métodos que se publicaron por año y sus aplicaciones. Abstract. Image complexity has been studied with the purpose to propose computational algorithms that may simulate the human behavior for applications in diverse image processing areas. This paper presents a survey of recently published image complexity methods. The paper describes a classification based on the used characteristics to determine image complexity followed by a brief explanation. 28 papers from 2005 to 2018 were analyzed. From this analysis, 34 methods were determined. These methods are based on computational and human approaches. The classification categories are edge information, color and/or intensity information, level of compression, combined, human criterion, and human reaction. The paper also describes the datasets commonly used to evaluate the methods. Finally, it is performed an analysis of the methods in each category, main used characteristics, amount of methods published by year and their applications. Keywords: Image Complexity, Visual Complexity, Image Complexity Applications, Eye Tracking, EEG, MEG.

Author Biographies

Luis Madrid Herrera, Instituto Tecnológico de Chihuahua

Obtuvo el grado de Ingeniero en Mecatrónica del Instituto Tecnológico Superior de Nuevo Casas Grandes en 2015 y el grado de Maestro en Ciencias en Ingeniería Electrónica del Instituto Tecnológico de Chihuahua en 2018. Actualmente, es estudiante de Doctorado en Ciencias en Ingeniería Electrónica del Instituto Tecnológico de Chihuahua. Su investigación es en el área de procesamiento digital de señales e imágenes, enfocado a complejidad de imágenes e interfaces cerebro computadora.

Mario Ignacio Chacón Murguía, Instituto Tecnológico de Chihuahua

Obtuvo el grado de Ingeniero Industrial en Electrónica, 1982, y el grado de Maestro en Ciencias en Ingeniería Electrónica, 1985 del Instituto Tecnológico de Chihuahua, México, y el grado de Doctor en Ciencias, 1998, de la Universidad Estatal de Nuevo México, EEUU. Ha desarrollado varios proyectos para varias compañías. Actualmente trabaja como Profesor Investigador en el Instituto Tecnológico de Chihuahua. Ha publicado más de 175 trabajos y publicado 3 libros. Su investigación actual incluye Visión por Computadora y procesamiento de imágenes y señales usando Inteligencia Computacional. El Dr. Chacón es miembro Senior de la IEEE, y miembro de las sociedades IEEE; Inteligencia computacional, Procesamiento Digital de Señales y Miembro del SNI en México.

Juan Alberto Ramírez Quintana, Instituto Tecnológico de Chihuahua

Recibió los grados de  ingeniero (2004), maestría (2007) y doctorado (2014) en ingeniería electrónica del Instituto Tecnológico de Chihuahua, México. Actualmente trabaja como profesor-investigador en el Instituto Tecnológico de Chihuahua. Sus áreas de interés son visión por computadora, procesamiento de señales, percepción visual, inteligencia computacional. El Dr. Ramírez es miembro del Sistema Nacional de Investigadores de México.

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Published

2018-10-31

How to Cite

Madrid Herrera, L., Chacón Murguía, M. I., & Ramírez Quintana, J. A. (2018). Análisis de Métodos de Medición de Complejidad de Imagen - Image Complexity Measurement Methods: A Survey. ReCIBE, Electronic Journal of Computing, Informatics, Biomedical and Electronics, 7(2), 17–46. https://doi.org/10.32870/recibe.v7i2.99

Issue

Section

Computer Science & IT