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Home > Archive>Volume 15, Issue 10, 2004 >1461-1469
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Algorithms of High-Level Semantic-Based Image Retrieval
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    Abstract:

    IPSM is an integrated probabilistic image semantic description multi-level model. This model includes input layer, feature layer, semantic layer, synthetical probability layer, probability propagation layer, and semantic mapping layer. Based on the model and characterizing of the image high-level semantic content according to Bayesian theory, SHM (semantic high-level retrieval algorithm) and SRF (high-level semantic relevance feedback) for image retrieval based on high-level semantic content, for user relevance feedback respectively, are designed and implemented. Experimental results indicate that IPSM, SHM and SRF are effective in characterizing image high-level semantic content and can provide sound and robust image retrieval performance.

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王崇骏,杨育彬,陈世福.基于高层语义的图像检索算法.软件学报,2004,15(10):1461-1469

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  • Received:July 07,2003
  • Revised:February 03,2004
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