Vast collections of documents available in image format need to be indexed for information
retrieval purposes. In this framework, word spotting is an alternative solution to optical …

In this work we present an end-to-end system for text spotting—localising and recognising
text in natural scene images—and text based image retrieval. This system is based on a …

This paper addresses the problems of word spotting and word recognition on images. In
word spotting, the goal is to find all instances of a query word in a dataset of images. In …

Providing computers with the ability to process handwriting is both important and
challenging, since many difficulties (eg, different writing styles, alphabets, languages, etc.) …

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 …

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 a segmentation-free word spotting method that is able to deal with
heterogeneous document image collections. We propose a patch-based framework where …

Line-level keyword spotting (KWS) is presented on the basis of frame-level word posterior
probabilities. These posteriors are obtained using word graphs derived from the recognition …

In this paper we propose an unsupervised segmentation-free method for word spotting in
document images. Documents are represented with a grid of HOG descriptors, and a sliding …

This paper proposes a novel similarity measure between vector sequences. We work in the
framework of model-based approaches, where each sequence is first mapped to a Hidden …