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Visual knowledge representation and intelligent image segmentation

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Abstract

Automatic medical image analysis shows that image segmentation is a crucial task for any practical AI system in this field. On the basis of evaluation of the existing segmentation methods, a new image segmentation method is presented. To seek the perfect solution to knowledge representation in low level machine vision, a new knowledge representation approach—“Notebook” approach is proposed and the processing of visual knowledge is discussed at all levels. To integrate the computer vision theory with Gestalt psychology and knowledge engineering, a new integrated method for intelligent image segmentation of sonargraphs—“Generalized-pattern guided segmentation” is proposed. With the methods and techniques mentioned above, the medical diagnosis expert system for sonargraphs can be built. The work on the preliminary experiments is also introduced.

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Authors and Affiliations

  1. Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, 710049, Xi'an

    Zheng Nanning & Liu Jianqin

Authors
  1. Zheng Nanning
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  2. Liu Jianqin
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Additional information

This work was supported by the National Natural Science Foundation of China.

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Zheng, N., Liu, J. Visual knowledge representation and intelligent image segmentation. J. of Comput. Sci. & Technol. 7, 219–225 (1992). https://doi.org/10.1007/BF02946571

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  • DOI: https://doi.org/10.1007/BF02946571

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