Data fusion in robotics and machine intelligence
Data fusion in robotics and machine intelligence
Multisensor image fusion using the wavelet transform
Graphical Models and Image Processing
Multisensor integration and fusion for intelligent machines and systems
Multisensor integration and fusion for intelligent machines and systems
Color edge extraction using orthogonal polynomials based zero crossings scheme
Information Sciences: an International Journal
Fundamentals of Uncertainty Calculi with Applications to Fuzzy Inference
Fundamentals of Uncertainty Calculi with Applications to Fuzzy Inference
Fuzzy Measure Theory
Color image processing by using binary quaternion-moment-preserving thresholding technique
IEEE Transactions on Image Processing
Applications of the ILF Paradigm in Image Processing
AFSS '02 Proceedings of the 2002 AFSS International Conference on Fuzzy Systems. Calcutta: Advances in Soft Computing
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This paper presents a new paradigm for image processing in multisensorial computer vision systems based on a new interpretation of the fuzzy integral as fusion operator. Fuzzy integrals offer great chances for the implementation of the fusion stage in multisensorial systems. By exploring these possibilities a new paradigm for image processing in the framework of information fusion in multisensorial systems can be established. This new paradigm, which can be designated as Intelligent Localized Fusion (ILF), is related to Soft-Computing methodologies and the object of this paper. The performance of intelligent localized fusion operators (ILFOs), which are developed under the new introduced paradigm, are exemplary shown in the case of color edge detection in outdoor scenes. Its usage allows in this case the avoidance of false edges due to the presence of shadows.