Keyword Retrieval Using Scale-Space Pyramid

Irina Rabaev, Klara Kedem, Jihad El-Sana

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

We propose a pyramid-based method for keyword spotting in historical document images. The documents are represented by a scale-space pyramid of their features. The search for a query keyword begins at the highest level of the pyramid, where the initial candidates for matching are located. The candidates are further refined at each level of the pyramid. The number of levels is adaptive and depends on the length of the query word. The results from all the document images are combined and ranked. We compare two feature representations, grid-based and continuous, and show that continuous feature representation outperforms the grid-based representation. In order to reduce the memory used to store the scale-space pyramid of features, we discuss and compare two compressing approaches. The proposed method was evaluated on four different collections of historical documents achieving state-of-the-art results.

Original languageEnglish
Title of host publicationProceedings - 12th IAPR International Workshop on Document Analysis Systems, DAS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages144-149
Number of pages6
ISBN (Electronic)9781509017928
DOIs
StatePublished - 10 Jun 2016
Event12th IAPR International Workshop on Document Analysis Systems, DAS 2016 - Santorini, Greece
Duration: 11 Apr 201614 Apr 2016

Publication series

NameProceedings - 12th IAPR International Workshop on Document Analysis Systems, DAS 2016

Conference

Conference12th IAPR International Workshop on Document Analysis Systems, DAS 2016
Country/TerritoryGreece
CitySantorini
Period11/04/1614/04/16

Keywords

  • spotting historical documents scale-space pyramid HOG features

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