Efficient symbol retrieval by building a symbol index from a collection of line drawings

Symbol retrieval is important for content-based search in digital libraries and for automatic interpretation of line drawings. In this work, we present a complete symbol retrieval system. The proposed system has an off-line content-analysis stage, where the contents of a database of line drawings are represented as a symbol index, which is a compact indexable representation of the database. Such representation allows efficient on-line query retrieval. Within the retrieval system, three methods are presented. First, a feature grouping method for identifying local regions of interest (ROIs) in the drawings. The found ROIs represent symbols' parts. Second, a clustering method based on geometric matching, is used to cluster the similar parts from all the drawings together. A symbol index is then constructed from the clusters' representatives. Finally, the ROIs of a query symbol are matched to the clusters' representatives. The matching symbols' parts are retrieved from the clusters, and spatial verification is performed on the matching parts. By using the symbol index we are able to achieve a query look-up time that is independent of the database size, and dependent on the size of the symbol index. The retrieval system achieves higher recall and precision than state-of-the-art methods.