A genetic algorithm for determining nonadditive set functions in information fusion
Fuzzy Sets and Systems - Special issue on fuzzy measures and integrals
Principles of visual information retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Detection in Color Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Fundamentals of Uncertainty Calculi with Applications to Fuzzy Inference
Fundamentals of Uncertainty Calculi with Applications to Fuzzy Inference
Statistical color models with application to skin detection
International Journal of Computer Vision
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Skin Color-Based Video Segmentation under Time-Varying Illumination
IEEE Transactions on Pattern Analysis and Machine Intelligence
Color seal extraction from documents: robustness through soft data fusion
EURASIP Journal on Applied Signal Processing
Identification of general fuzzy measures by genetic algorithmsbased on partial information
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Attentiveness assessment in learning based on fuzzy logic analysis
Expert Systems with Applications: An International Journal
Chance-constrained programming on sugeno measure space
Expert Systems with Applications: An International Journal
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Complex image processing tasks rarely succeed through the application of just one methodology. The implementation of different methodologies, whose treatment of the input images is complementary, can help in the successful attainment of the system goal. The result of the complementary procedures has to be eventually fused in order for the system to improve the result of each methodology taken on its own. Computer vision systems mostly employ simple fusion strategies for this aim. This simplicity downplays the relevance of the fusion stage. The paper presents a framework for skin detection, a pre-processing task very useful in application fields like video surveillance, human-machine interface, and cyber-crime prosecution. The framework is based on the employment of the fuzzy integral, which subsumes the performance of more simple fusion operators. As it is shown herein the framework manages therefore to cope with the complexity of skin detection under changing illumination conditions. The performance evaluation of the framework is undertaken on hand of a benchmark database in the paper.