Análisis de Métodos de Medición de Complejidad de Imagen - Image Complexity Measurement Methods: A Survey
DOI:
https://doi.org/10.32870/recibe.v7i2.99Palabras clave:
Image Complexity, Visual Complexity, Image Complexity Applications, Eye Tracking, EEG, MEGResumen
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.Citas
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