Histogram equalization based on the fuzzy local fittingness

Marco A. García; Cherif Ben-Youssef; Ramón Soto C.

doi:10.1142/9789814619998_0070

Histogram equalization based on the fuzzy local fittingness

Marco A. García, Cherif Ben-Youssef, Ramón Soto C.

Departamento de Contabilidad

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Histogram modification techniques are an important tool for image enhancement. However, the efficiency of most of these techniques is limited due to the lack of mechanisms to differentiate between pixels that have the same intensity but belong to regions which are semantically distinct. In this paper, a method for histogram equalization, able to selectively modify each pixel in a digital image based on the context established by its neighboring pixels is proposed. This method emulates the decision–making process used by living organisms to recognize patterns, as described by the Gestalt theory.

Original language	English
Title of host publication	Decision Making and Soft Computing - Proceedings of the 11th International FLINS Conference, FLINS 2014
Editors	Ronei Marcos de Moraes, Etienne E. Kerre, Liliane dos Santos Machado, Jie Lu
Publisher	World Scientific Publishing Co. Pte Ltd
Pages	418-423
Number of pages	6
ISBN (Electronic)	9789814619967
DOIs	https://doi.org/10.1142/9789814619998_0070
State	Published - 2014
Event	Decision Making and Soft Computing - 11th International Fuzzy Logic and Intelligent Technologies in Nuclear Science Conference, FLINS 2014 - Joao Pessoa, Paraiba, Brazil Duration: 17 Aug 2014 → 20 Aug 2014

Publication series

Name	Decision Making and Soft Computing - Proceedings of the 11th International FLINS Conference, FLINS 2014

Conference

Conference	Decision Making and Soft Computing - 11th International Fuzzy Logic and Intelligent Technologies in Nuclear Science Conference, FLINS 2014
Country/Territory	Brazil
City	Joao Pessoa, Paraiba
Period	17/08/14 → 20/08/14

Bibliographical note

Publisher Copyright:
© 2014 by World Scientific Publishing Co. Pte. Ltd. All rights reserved.

Access to Document

10.1142/9789814619998_0070

Cite this

García, M. A., Ben-Youssef, C., & Soto C., R. (2014). Histogram equalization based on the fuzzy local fittingness. In R. M. de Moraes, E. E. Kerre, L. dos Santos Machado, & J. Lu (Eds.), Decision Making and Soft Computing - Proceedings of the 11th International FLINS Conference, FLINS 2014 (pp. 418-423). (Decision Making and Soft Computing - Proceedings of the 11th International FLINS Conference, FLINS 2014). World Scientific Publishing Co. Pte Ltd. https://doi.org/10.1142/9789814619998_0070

García, Marco A. ; Ben-Youssef, Cherif ; Soto C., Ramón. / Histogram equalization based on the fuzzy local fittingness. Decision Making and Soft Computing - Proceedings of the 11th International FLINS Conference, FLINS 2014. editor / Ronei Marcos de Moraes ; Etienne E. Kerre ; Liliane dos Santos Machado ; Jie Lu. World Scientific Publishing Co. Pte Ltd, 2014. pp. 418-423 (Decision Making and Soft Computing - Proceedings of the 11th International FLINS Conference, FLINS 2014).

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title = "Histogram equalization based on the fuzzy local fittingness",

abstract = "Histogram modification techniques are an important tool for image enhancement. However, the efficiency of most of these techniques is limited due to the lack of mechanisms to differentiate between pixels that have the same intensity but belong to regions which are semantically distinct. In this paper, a method for histogram equalization, able to selectively modify each pixel in a digital image based on the context established by its neighboring pixels is proposed. This method emulates the decision–making process used by living organisms to recognize patterns, as described by the Gestalt theory.",

author = "Garc{\'i}a, {Marco A.} and Cherif Ben-Youssef and {Soto C.}, Ram{\'o}n",

note = "Publisher Copyright: {\textcopyright} 2014 by World Scientific Publishing Co. Pte. Ltd. All rights reserved.; Decision Making and Soft Computing - 11th International Fuzzy Logic and Intelligent Technologies in Nuclear Science Conference, FLINS 2014 ; Conference date: 17-08-2014 Through 20-08-2014",

year = "2014",

doi = "10.1142/9789814619998_0070",

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series = "Decision Making and Soft Computing - Proceedings of the 11th International FLINS Conference, FLINS 2014",

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pages = "418--423",

editor = "{de Moraes}, {Ronei Marcos} and Kerre, {Etienne E.} and {dos Santos Machado}, Liliane and Jie Lu",

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García, MA, Ben-Youssef, C & Soto C., R 2014, Histogram equalization based on the fuzzy local fittingness. in RM de Moraes, EE Kerre, L dos Santos Machado & J Lu (eds), Decision Making and Soft Computing - Proceedings of the 11th International FLINS Conference, FLINS 2014. Decision Making and Soft Computing - Proceedings of the 11th International FLINS Conference, FLINS 2014, World Scientific Publishing Co. Pte Ltd, pp. 418-423, Decision Making and Soft Computing - 11th International Fuzzy Logic and Intelligent Technologies in Nuclear Science Conference, FLINS 2014, Joao Pessoa, Paraiba, Brazil, 17/08/14. https://doi.org/10.1142/9789814619998_0070

Histogram equalization based on the fuzzy local fittingness. / García, Marco A.; Ben-Youssef, Cherif; Soto C., Ramón.
Decision Making and Soft Computing - Proceedings of the 11th International FLINS Conference, FLINS 2014. ed. / Ronei Marcos de Moraes; Etienne E. Kerre; Liliane dos Santos Machado; Jie Lu. World Scientific Publishing Co. Pte Ltd, 2014. p. 418-423 (Decision Making and Soft Computing - Proceedings of the 11th International FLINS Conference, FLINS 2014).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Ben-Youssef, Cherif

AU - Soto C., Ramón

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N2 - Histogram modification techniques are an important tool for image enhancement. However, the efficiency of most of these techniques is limited due to the lack of mechanisms to differentiate between pixels that have the same intensity but belong to regions which are semantically distinct. In this paper, a method for histogram equalization, able to selectively modify each pixel in a digital image based on the context established by its neighboring pixels is proposed. This method emulates the decision–making process used by living organisms to recognize patterns, as described by the Gestalt theory.

AB - Histogram modification techniques are an important tool for image enhancement. However, the efficiency of most of these techniques is limited due to the lack of mechanisms to differentiate between pixels that have the same intensity but belong to regions which are semantically distinct. In this paper, a method for histogram equalization, able to selectively modify each pixel in a digital image based on the context established by its neighboring pixels is proposed. This method emulates the decision–making process used by living organisms to recognize patterns, as described by the Gestalt theory.

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DO - 10.1142/9789814619998_0070

M3 - Contribución a la conferencia

AN - SCOPUS:85037345014

T3 - Decision Making and Soft Computing - Proceedings of the 11th International FLINS Conference, FLINS 2014

SP - 418

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BT - Decision Making and Soft Computing - Proceedings of the 11th International FLINS Conference, FLINS 2014

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A2 - Kerre, Etienne E.

A2 - dos Santos Machado, Liliane

A2 - Lu, Jie

PB - World Scientific Publishing Co. Pte Ltd

T2 - Decision Making and Soft Computing - 11th International Fuzzy Logic and Intelligent Technologies in Nuclear Science Conference, FLINS 2014

Y2 - 17 August 2014 through 20 August 2014

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García MA, Ben-Youssef C, Soto C. R. Histogram equalization based on the fuzzy local fittingness. In de Moraes RM, Kerre EE, dos Santos Machado L, Lu J, editors, Decision Making and Soft Computing - Proceedings of the 11th International FLINS Conference, FLINS 2014. World Scientific Publishing Co. Pte Ltd. 2014. p. 418-423. (Decision Making and Soft Computing - Proceedings of the 11th International FLINS Conference, FLINS 2014). doi: 10.1142/9789814619998_0070

Histogram equalization based on the fuzzy local fittingness

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