Word Indexing of Ancient Documents Using Fuzzy Classification

This paper proposes a fuzzy classification system to perform word indexing in ancient printed documents. The indexing system receives a given word selected by an user. The word is preprocessed using an aspect ratio filter, assuring that only interesting word candidates are considered. The image is classified by oriented feature extraction using Gabor filter banks. The oriented features are used to generate membership functions that characterize the selected word. This target word image is then compared to the potential matches, using a similarity matrix. The indexing system is flexible and lightweight when compared to other optimal recognizers, which allows its use in "real-time" applications. A significant test revealed that the indexer achieved very good results in terms of precision and recall in texts from XVIIth century.