Abstract
This article presents Ottoman Archives Explorer, a Content-Based Retrieval (CBR) system based on character recognition for printed and handwritten historical documents. Several methods for character segmentation and recognition stages are investigated. In particular, sliding-window and histogram segmentation methods are coupled with recognition approaches using spatial features, neural networks, and a graph-based model. The prototype system provides CBR of document images using both example-based queries and a virtual keyboard to construct query words.
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