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In this paper, we present a fast text retrieval system to index and browse degraded historical documents. The indexing and retrieval strategy is designed in a two level, coarse-to-fine approach, to increase the speed of the retrieval process. During the indexing step, the text parts in the images are encoded into sequences of primitives, obtained from two different codebooks: a coarse one corresponding to connected components and a fine one corresponding to glyph primitives. A glyph consists of a single character or a part of a character according to the shape complexity. During the querying step, the coarse and the fine signature are generated from the query image using both codebooks. Then, a bi-level approximate string matching algorithm is applied to find similar words, using coarse approach first, and then the fine approach if necessary, by exploiting predetermined hypothetical locations. An experimental evaluation on datasets of real life document images, gathered from historical books of different scripts, demonstrated the speed improvement and good accuracy in presence of degradation.