Bio-Inspired Optimization of a Fuzzy System Inference for the Generation of Psychedelic Effects in Digital Images

Authors

  • Linda Rodríguez Universidad Distrital Bogotá
  • Iván Ponce Universidad Distrital Bogotá
  • Helbert Espitia Universidad Distrital Bogotá

Keywords:

Evolutionary art, colorimetry, fuzzy logic, fuzzy sets, image processing, optimization

Abstract

The generation of effects on digital images through computers has created a new age for different artistic trends. Particularly, the digital age has had a remarkable impact on psychedelic art. In this paper we propose a fuzzy inference system for color manipulation in digital images with the purpose of modifying their artistic style. The proposed system aims to create a combination of different colors to generate a new visual sensation, much like the current psychedelic art. The proposed system is divided into two parts. The first part of the method consists in the creation of a fuzzy logic system that, through fuzzy sets, and rules of change generates color images that produced this psychedelic effect. In the second part, the differential evolution algorithm optimizes parameters of the proposed inference system and adjusts the results to the psychedelic art style used.

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References

S. Dipaola, L. Gabora. “Incorporating Characteristics of Human Creativity into an Evolutionary Art Algorithm”. Genetic Programming and Evolvable Machines, Vol 10, No 2, pp 97-110. June 2009.

L. Yang, "Adaptive learning evaluation model for evolutionary art," 2012 IEEE Congress on Evolutionary Computation (CEC), pp.1,8, 10-15 June 2012

M. Davoudi, M. Davoudi, N. Seifnaraghi, "Adaptive Subtitle and Caption Coloring Using Fuzzy Analysis", 2009 WRI World Congress on Computer Science and Information Engineering, vol.4, pp.764,768, 2009.

T. Celik, H. Ozkaramanli, H. Demirel, "Fire Pixel Classification using Fuzzy Logic and Statistical Color Model" IEEE International Conference on Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. , vol.1, pp.I-1205,I-1208, April 2007

C. Millet, I. Bloch, A. Popescu, “Using the Knowledge of Object Colors to Segment Images and Improve Web Image Search”, Large Scale Semantic Access to Content (Text, Image, Video, and Sound), Le Centre De Hautes Etudes Internationales D’informatique Documentaire. ACM Special Interest Group on Information Retrieval. Pp 569-584.

M.E. Yuksel, A. Basturk, "Application of Type-2 Fuzzy Logic Filtering to Reduce Noise in Color Images" IEEE Computational Intelligence Magazine, vol.7, no.3, pp.25,35, Aug. 2012

F. Chung, B. Fung, . “Fuzzy Color Quantization and its Application to Scene Change Detection”. Conference International Multimedia Conference ACM. New York, NY, USA, 2003.

A. Borji, M. Hamidi, “Evolving a Fuzzy Rule-Base for Image Segmentation”. International Journal of Intelligent Technology. No 2, Vol 3, pp 471-476, 2007.

P. Khanale, A. Kurhe. Color Perception of Images Using Fuzzy Logic. Advances in Computational Sciences and Technology. Vol 4, No 1 , pp 1-8, 2011.

O. Jung-Min, B. Bang, G. Lee. “Personal Color Decision System Using Fuzzy Logic”. International Conference on Convergence and Hybrid Information Technology. Daejeon. Pp 790-795,2008.

Universidad de Extremadura. (2012). “Aplicaciones de la lógica difusa a la colorimetría”. Revista Hiperenciclopédica de Divulgación del Saber, Vol 6, No 4.

T. Terano, S. Masui, H. Watanabe. “Coloring of a Landscape by Fuzzy Logic”. IEEE International Conference on Fuzzy Systems, pp 13-20,1992.

E. Luft. Die at the Right Time! A Subjective Cultural History of the American Sixties. United States: United Book Press, 1952.

C. D ́Negri, E. De Vitro. “Introducción al Razonamiento Aproximado: Lógica Difusa”. Revista Argentina de Medicina Respiratoria. Vol 4, pp 126-136, 2006.

E. Alba, M. Laguna, R. Martí. “Métodos evolutivos en problemas de optimización”. Revista INGENIERíA UC, Vol 10, No 3, pp 80-89, 2003.

T. Young. “The Bakerian Lecture: On the Theory of Light and Colours”. Phil. Trans. R. Soc. Lond, pp 12-48, 1802.

L. Zadeh. “Fuzzy Sets”. Information and Control. Vol 8. Pp 338- 353, 1965.

T. Weise. Global optimization algorithms theory and application. Self-Published Thomas Weise, 2009.

L. Rodríguez, I. Ponce, H. Espitia. °Propuesta y Ajuste de un Sistema de Inferencia Difusa para la Ganeración de Efectos Psicodélicos en Imágenes Digitales°. XVIII STSIVA, 2013.

R. Storn, K. Price. “Differential evolution a simple and efficient heuristic for global optimization over continuous spaces”. Journal of Global Optimization, Vol 11, No 4, pp 341-359, 1997.

K. Price, R. Storn, J. Lampinen. “Differential Evolution A Practical Approach to Global Optimization”. Natural Computing Series. Springer-Verlag, Berlin, 2005.

O. Ramírez. “Simulación en simmechanics de un sistema de control difuso para el robot udlap”. Tesis Licenciatura. Ingeniería Mecatrónica. Departamento de Computación, Electrónica y Mecatrónica, Escuela de Ingeniería y Ciencias, Universidad de las Américas Puebla. Junio 2008.

Published

2014-09-08
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How to Cite

Rodríguez, L., Ponce, I., & Espitia, H. (2014). Bio-Inspired Optimization of a Fuzzy System Inference for the Generation of Psychedelic Effects in Digital Images. INGE@UAN - TENDENCIAS EN LA INGENIERÍA, 4(8). Retrieved from https://revistas.uan.edu.co/index.php/ingeuan/article/view/373

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Artículo de investigación científica y tecnológica

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