JACIII Vol.8 No.1 pp. 29-38
doi: 10.20965/jaciii.2004.p0029


Dynamic Color Object Recognition Using Fuzzy Logic

Napoleon H. Reyes* and Elmer P. Dadios**

*College of Computer Studies 2401 Taft Avenue, De La Salle University, Manila, 1004 Philippines

**Department of Manufacturing Engineering and Management 2401 Taft Avenue, De La Salle University, Manila, 1004 Philippines

June 25, 2003
September 9, 2003
January 20, 2004
dynamic color object recognition, color constancy, contrast operators, Logit-Logistic Fuzzy Color Constancy Algorithm (LLFCC)

This paper presents a novel Logit-Logistic Fuzzy Color Constancy (LLFCC) algorithm and its variants for dynamic color object recognition. Contrary to existing color constancy algorithms, the proposed scheme focuses on manipulating a color locus depicting the colors of an object, and not stabilizing the whole image appearance per se. In this paper, a new set of adaptive contrast manipulation operators is introduced and utilized in conjunction with a fuzzy inference system. Moreover, a new perspective in extracting color descriptors of an object from the rg-chromaticity space is presented. Such color descriptors allow for the reduction of the effects of brightness/darkness and at the same time adhere to human perception of colors. The proposed scheme tremendously cuts processing time by simultaneously compensating for the effects of a multitude of factors that plague the scene of traversal, eliminating the need for image pre-processing steps. Experiment results attest to its robustness in scenes with multiple white light sources, spatially varying illumination intensities, varying object position, and presence of highlights.

Cite this article as:
Napoleon H. Reyes and Elmer P. Dadios, “Dynamic Color Object Recognition Using Fuzzy Logic,” J. Adv. Comput. Intell. Intell. Inform., Vol.8, No.1, pp. 29-38, 2004.
Data files:

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Mar. 01, 2021