Abstract
Feature extraction and similarity measure are two basickey issues in image retrieval. Combining the advantages of SNNin image recognition and selective attention for image retrieval,a novel visual keywords-driven image retrieval approach basedon these properties has been proposed. By using a predefinedset of visual keywords as prototype patterns stored with theSNN and then measuring the degree of similiarity of the storedimages to the visual keywords, we show that such a visual keyworddriven SNN can provide the framework for image indexing or retrievalwhich is scalable, robust and efficient for web-based search.
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Zhao, T., Tang, L.H., Ip, H.H.S. et al. Visual Keyword Image Retrieval Based on Synergetic Neural Network for Web-Based Image Search. Real-Time Systems 21, 127–142 (2001). https://doi.org/10.1023/A:1011147421401
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DOI: https://doi.org/10.1023/A:1011147421401