LAMP Seminar
Language and Media Processing Laboratory
Conference Room 4406
A.V. Williams Building
University of Maryland

SEPTEMBER 22, 1998, 1:00
Dr. Ronald A. Riley and Dr. Narbik Manukian

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Author Recognition and Keyword Spotting in Handwritten Documents


We present new techniques and results for word recognition and for writer identification from handwritten documents. These problems are complementary and require the development of features that depend on word content but are independent of stylistic variations for the first problem and depend on style but are independent of content for the second. Accordingly, we have developed both a set of style-dependent features and a set of style-independent features. These features have been applied to two handwritten document databases: 1) a signature database collected from company timecards for word recognition and 2) a Chinese document database. Results are presented for both. For word recognition, we present a new metric for invariant image recognition. This metric can be used to accurately recognize objects in spite of the presence of noise, distortions in the shape of the image, and clutter which overlaps and obscures parts of the object. For writer identification, we present a novel method of unsupervised clustering of documents based on the handwriting style of their authors.

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