For retrieving keywords from scanned handwritten documents, we present a word spotting
system that is based on character Hidden Markov Models. In an efficient lexicon-free …

Searching and indexing historical handwritten collections are a very challenging problem.
We describe an approach called word spotting which involves grouping word images into …

Keyword spotting refers to the process of retrieving all instances of a given keyword from a
document. In the present paper, a novel keyword spotting method for handwritten …

In this paper we present an efficient segmentation-free word spotting method, applied in the
context of historical document collections, that follows the query-by-example paradigm. We …

Handwritten word-spotting is traditionally viewed as an image matching task between one or
multiple query word-images and a set of candidate word-images in a database. This is a …

In this work, a multi-scale binarization framework is introduced, which can be used along
with any adaptive threshold-based binarization method. This framework is able to improve …

In this article we introduce a text search algorithm designed for ancient manuscripts. Word-
spotting is the best alternative to word recognition on this type of document. Our method is …

In this article, we introduce the first method that allows the indexation of ancient manuscripts
of any language and alphabet. We describe a word retrieval engine inspired by recent word …

Abstract The Bag-of-Visual-Words (BoVW) framework has gained popularity among the
document image analysis community, specifically as a representation of handwritten words …

Word spotting is the process of retrieving all instances of a queried keyword from a digital
library of document images. In this paper we evaluate the performance of different word …