Ink retrieval from handwritten documents

Abstract

This paper compares several information retrieval (IR) methods applied to the problem of retrieving specific words from a handwritten document. The methods compared include variants of the Okapi formula and Latent Semantic Indexing (LSI); recognition-based retrieval; and keyword search. One novel aspect of the work presented is that it uses the output stack of a Hidden Markov Model (HMM) handwriting recognizer with a 30,000-word lexicon to convert each handwritten word into a document which is then used for document retrieval. Preliminary experiments on a database of 1158 words from 75 writers indicate that the keyword search has superior precision and recall for text queries, and that ink queries result in minor performance reductions.