On some fuzzy relations for color information

In this paper we introduce several fuzzy resemblance relations between different combinations of crisp and fuzzy colors. As a starting point, we discuss about fuzzy colors and fuzzy color spaces as a way to represent color information, providing examples of conjunctive and disjunctive use of fuzzy colors for this purpose. Then we determine different types of relations measuring the degree of matching between color information of different kinds, using well known results from fuzzy sets and possibility theories. We study the particular case in which the user considers there is no resemblance between the fuzzy colors comprising the fuzzy color space under consideration. The proposal is based on definitions of fuzzy color and fuzzy color space provided by the authors in previous works.

[1]  J. Lammens.  A computational model of color perception and color naming , 1995 .

[2]  Jesús Chamorro-Martínez,et al.  Fuzzy Homogeneity Measures for Path-Based Colour Image Segmentation , 2005, The 14th IEEE International Conference on Fuzzy Systems, 2005. FUZZ '05..

[3]  Nicolas Plouznikoff,et al.  Enhancing human-machine interactions: virtual interface alteration through wearable computers , 2006, CHI.

[4]  Herman Akdag,et al.  Color Image Profiling Using Fuzzy Sets , 2005 .

[5]  P. Kay,et al.  The linguistic significance of the meanings of basic color terms , 1978 .

[6]  Naotoshi Sugano.  Fuzzy Set Theoretical Approach to the RGB Color Triangle , 2006, KES.

[7]  Didier Dubois,et al.  Gradualness, uncertainty and bipolarity: Making sense of fuzzy sets , 2012, Fuzzy Sets Syst..

[8]  D. Dubois,et al.  Incomplete conjunctive information , 1988 .

[9]  Chris Cornelis,et al.  Sinha-Dougherty approach to the fuzzification of set inclusion revisited , 2003, Fuzzy Sets Syst..

[10]  A. Mojsilovi.  A Computational Model for Color Naming and Describing Color Composition of Images , 2022 .

[11]  Neamat El Gayar,et al.  A new approach in content-based image retrieval using fuzzy , 2009, Telecommun. Syst..

[12]  Daniel Sánchez,et al.  Region-based fit of color homogeneity measures for fuzzy image segmentation , 2007, Fuzzy Sets Syst..

[13]  Daniel Sánchez,et al.  Describing images via linguistic features and hierarchical segmentation , 2010, International Conference on Fuzzy Systems.

[14]  Daniel Sánchez,et al.  A new approach for defining a fuzzy color space , 2010, International Conference on Fuzzy Systems.

[15]  Didier Dubois,et al.  On incomplete conjunctive information , 1988, Int. J. Approx. Reason..

[16]  Ronald R. Yager,et al.  Set-based representations of conjunctive and disjunctive knowledge , 1987, Inf. Sci..

[17]  M. Vanrell,et al.  Parametric fuzzy sets for automatic color naming. , 2008, Journal of the Optical Society of America. A, Optics, image science, and vision.

[18]  Naotoshi Sugano,et al.  Color-naming system using fuzzy set theoretical approach , 2001, 10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297).

[19]  Ismat Beg,et al.  SIMILARITY MEASURES FOR FUZZY SETS , 2009 .

[20]  Lotfi A. Zadeh,et al.  A New Direction in AI: Toward a Computational Theory of Perceptions , 2001, AI Mag..

[21]  Yong Yu,et al.  Deep into Color Names: Matching Color Descriptions by Their Fuzzy Semantics , 2006, AIMSA.

[22]  A. L..  PRUF a meaning representation language for natural languages , 2008 .

[23]  José M. Soto-Hidalgo,et al.  Retrieving images in fuzzy object-relational databases using dominant color descriptors , 2007, Fuzzy Sets Syst..