Along with the explosive growth of the amount of handwritten documents that are preserved, processed and accessed in a digital form, handwritten document images word spotting has attracted many researchers of various research communities, such as pattern recognition, computer vision and information retrieval. Work on the problem of handwritten documents word spotting has been an active research area and significant progress has been made in the last few years. However, in spite of the great progress achieved, handwritten document word spotting still can hardly achieve acceptable performance on real-world handwritten document images that vary widely in writing style and quality. This paper gives an overview of published research efforts in the area of handwritten document image word spotting and on the technologies used in the field. We first start by describing a general model for document word spotting followed by discussing present challenges in handwritten document word spotting. Then the used databases for handwritten document word spotting and other handwritten text tasks are discussed. After that, research works on handwritten document word spotting are presented. Finally, several summary tables of published research work are provided for used handwritten documents databases and reported performance results on handwritten documents word spotting. These tables summarize different aspects and the reported accuracy for each technique.
|Number of pages||17|
|Journal||International Journal of Multimedia Information Retrieval|
|State||Published - 1 Mar 2017|
Bibliographical notePublisher Copyright:
© 2016, Springer-Verlag London.
- Content-based image retrieval (CBIR)
- Documents indexing
- Documents retrieval
- Historical documents word spotting
- Word spotting
ASJC Scopus subject areas
- Information Systems
- Media Technology
- Library and Information Sciences