PyFCS GUI: A new visualization and interaction framework for fuzzy color spaces

A new graphical user interface (GUI) has been developed as an extension to the open-source PyFCS library for constructing and analyzing fuzzy color spaces. This GUI improves usability and accessibility by allowing users to generate fuzzy color spaces from palettes or images, visualize them interactively in 3D, and perform advanced color mapping. Parametric controls enable users to explore various levels of generalization and specificity in the color modeling process. The resulting fuzzy color spaces can be exported in reusable formats to promote reproducibility. This extension significantly enhances the practical applicability of fuzzy color models, providing a versatile tool for both scientific research and artistic or perceptual analysis.

Authors

Institutions

Publication Details

Journal
SoftwareX
Published
2025-09-01
DOI
https://doi.org/10.1016/j.softx.2025.102316
Primary Topic
Image Retrieval and Classification Techniques
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

PyFCS GUI: A new visualization and interaction framework for fuzzy color spaces

María Tejada-Casado, Razvan Ghinea, J. M. Soto-Hidalgo, Luis Javier Herrera et al.
SoftwareX
Image Retrieval and Classification Techniques
article

PyFCS GUI: A new visualization and interaction framework for fuzzy color spaces

María Tejada-Casado, Razvan Ghinea, J. M. Soto-Hidalgo, Luis Javier Herrera, Rafael Vazquez-Conejo
article en

Abstract

A new graphical user interface (GUI) has been developed as an extension to the open-source PyFCS library for constructing and analyzing fuzzy color spaces. This GUI improves usability and accessibility by allowing users to generate fuzzy color spaces from palettes or images, visualize them interactively in 3D, and perform advanced color mapping. Parametric controls enable users to explore various levels of generalization and specificity in the color modeling process. The resulting fuzzy color spaces can be exported in reusable formats to promote reproducibility. This extension significantly enhances the practical applicability of fuzzy color models, providing a versatile tool for both scientific research and artistic or perceptual analysis.

SoftwareXVol. 31
Universidad de Granada (ES), Instituto de Investigación Biosanitaria de Granada (ES), Centre for Automation and Robotics (ES)
Ministerio de Ciencia e Innovación, European Regional Development Fund
Openalex Percentile: Top 77%
Image Retrieval and Classification Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.