@inproceedings{67876b1ad12f4116b3327765c45c6ad5,
title = "Keyword Retrieval Using Scale-Space Pyramid",
abstract = "We propose a pyramid-based method for keyword spotting in historical document images.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 The proposed method was evaluated on four different collections of historical documents achieving state-of-the-art results.",
keywords = "spotting historical documents scale-space pyramid HOG features",
author = "Irina Rabaev and Klara Kedem and Jihad El-Sana",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 12th IAPR International Workshop on Document Analysis Systems, DAS 2016 ; Conference date: 11-04-2016 Through 14-04-2016",
year = "2016",
month = jun,
day = "10",
doi = "10.1109/DAS.2016.16",
language = "English",
series = "Proceedings - 12th IAPR International Workshop on Document Analysis Systems, DAS 2016",
publisher = "Institute of Electrical and Electronics Engineers",
pages = "144--149",
booktitle = "Proceedings - 12th IAPR International Workshop on Document Analysis Systems, DAS 2016",
address = "United States",
}