ABSTRACT
The complexity of search in current business intelligence systems, academic research, or even the home audiovisual databases grows up rapidly. Users require searching by the content of their data. For example, the user sees a cathedral while watching a movie and by taking a snapshot, his or her private collection of holiday photos can be searched for images containing that cathedral, as demonstrated in Figure 1. In practice, it is not sufficient to store data and search in it by exact match but rather by means of similarity, i.e. retrieving data items similar to a query item. Similarity searching is especially requested in multimedia databases, digital right management systems, computer aided diagnosis, but also in natural sciences and psychology. In these fields, theoretical primal background for querying by similarity is already defined.
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Index Terms
- Sub-image searching through intersection of local descriptors
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