Image retrieval using fuzzy relevance feedback and validation with MPEG-7 content descriptors
PReMI'07 Proceedings of the 2nd international conference on Pattern recognition and machine intelligence
Interactive image retrieval with wavelet features
PReMI'11 Proceedings of the 4th international conference on Pattern recognition and machine intelligence
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Content-based image search has long been considered a difficult task. Making correct conjectures on the user intention (perception) based on the query images is a critical step in the content-based search. One key concept in this paper is how we find the user preferred low-level image characteristics from the multiple positive samples provided by the user. The second key concept is how we generate a set of consistent "pseudo images" when the user does not provide a sufficient number of samples. The notion of image feature stability is thus introduced. The third key concept is how we use negative images as pruning criterion. In realizing the preceding concepts, an image search scheme is developed using the weighted low-level image features. At the end, quantitative simulation results are used to show the effectiveness of these concepts.