Automatic Keyword Extraction from Historical Document Images

Abstract

Abstract. This paper presents an automatic keyword extraction method from historical document images. The proposed method is language independent because it is purely appearance based, where neither lexical information nor any other statistical language models are required. Moreover, since it does not need word segmentation, it can be applied to Eastern languages where they do not put clear spacing between words. The first half of the paper describes the algorithm to retrieve document image regions which have similar appearance to the given query image. The algorithm was evaluated in recall-precision manner, and showed its performance of over 80-90% average precision. The second half of the paper describes the keyword extraction method which works even if no query word is explicitly specified. Since the computational cost was reduced by the efficient pruning techniques, the system could extract keywords successfully from relatively large documents.

A line-based representation for matching words in historical manuscripts

“…In (Rothfeder et al, 2003) word images are matched based on the corresponding interest points. The other studies on word spotting and retrieval include (Terasawa et al, 2006;Sankar and Jawahar, 2006;Llados et al, 2007).…”

Generic Scale-Space Architecture for Handwriting Documents Analysis

“…Fink and Plotz in (Fink & Plotz, 2005) have tested appearancebased features for writer independent handwritten text recognition and compared it with heuristic features. Terasawa et al in (Terasawa et al, 2006) have developed principal component analysis-based descriptors and gradient distribution features for word spotting in historical handwritten documents. The only limitation of the approach is its application to only well segmented threshold documents and very regular handwritten texts.…”

Document image analysis for active reading

“…An occurrence of this word is found when a sub-image of the data set matches the query image. The features that are extracted from the word image can greatly differ from one matching method to another [29,30].…”