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 …

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 …

This paper presents a systematic literature review of image datasets for document image
analysis, focusing on historical documents, such as handwritten manuscripts and early …

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context of historical document collections, that follows the query-by-example paradigm.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 …

This paper addresses the problem of learning word image representations: given the
cropped image of a word, we are interested in finding a descriptive, robust, and compact …

Recognizing text in images taken in the wild is a challenging problem that has received
great attention in recent years. Previous methods addressed this problem by first detecting …

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 …

Recent HMM-based approaches to handwritten word spotting require large amounts of
learning samples and mostly rely on a prior segmentation of the document. We propose to …

From the early days of pattern recognition, word spotting have been important test beds for
studying how well machines can perform better decision making. In recent years, word …

A simple and efficient pipeline for word spotting in handwritten documents is proposed. The
method allows for extremely rapid querying, while still maintaining high accuracy. The …