Design Of Contentbased Retrieval Systems

Before discussing design issues, a conceptual architecture for content-based retrieval is introduced and illustrated in Figure 1.

Content-based retrieval uses the contents of multimedia to represent and index the data (Wei & Li, 2004). In typical content-based retrieval systems, the contents ofthe media in the database are extracted and described by multi-dimensional feature vectors, also called descriptors. The feature vectors of the media constitute a feature dataset. To retrieve desired data, users submit query examples to the retrieval system. The system then represents these examples with feature vectors. The distances (i.e., similarities) between the feature vectors of the query example and

Figure 1. A conceptual architecture for content-based retrieval

Query Example


Result Display


Feature Extraction

j y-


Ranking j *

Similarity Measure

those of the media in the feature dataset are then computed and ranked. Retrieval is conducted by applying an indexing scheme to provide an efficient way to search the media database. Finally, the system ranks the search results and then returns the top search results that are the most similar to the query examples.

For the design of content-based retrieval systems, a designer needs to consider four aspects: feature extraction and representation, dimension reduction of feature, indexing, and query specifications, which will be introduced in the following sections.

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