Paper
29 December 2008 Fuzzy spatial objects modeling from image based on fuzzy neural network
Author Affiliations +
Proceedings Volume 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA); 72853G (2008) https://doi.org/10.1117/12.815920
Event: International Conference on Earth Observation Data Processing and Analysis, 2008, Wuhan, China
Abstract
Traditional modeling methods on spatial objects are not eligible to deal well with the fuzzy features that acquired from image, some research need to be carried out on the fuzzy spatial objects modeling. With the deep investigation on the spatial objects model of GIS and the representation of natural geographical feature, fuzzy spatial objects have been proposed by researchers. Referring to the characteristics of the representation of fuzzy spatial objects, a generation method of fuzzy spatial objects based on fuzzy Neural Networks is going to be demonstrated by the authors in this paper. By combining the fuzzy technique and neural networks, utilizing the learning ability to enhance the fuzzy membership function and fuzzy rules, the system will be self-Adaptive. By comparing with the traditional fuzzy objects generation, the method in this paper improves the accuracy of results according to the experiments in this paper.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhongyuan Wang, Qingwen Qi, Zongyi He, and Ping Yang "Fuzzy spatial objects modeling from image based on fuzzy neural network", Proc. SPIE 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853G (29 December 2008); https://doi.org/10.1117/12.815920
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KEYWORDS
Fuzzy logic

Neural networks

Remote sensing

Fuzzy systems

Data processing

Image processing

Brain

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