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International Journal on Document Analysis and Recognition (IJDAR)

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01.08.2019 | Original Paper

Evaluation of word spotting under improper segmentation scenario

verfasst von: Sounak Dey, Anguelos Nicolaou, Josep Lladós, Umapada Pal

Erschienen in: International Journal on Document Analysis and Recognition (IJDAR) | Ausgabe 4/2019

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Abstract

Word spotting is an important recognition task in large-scale retrieval of document collections. In most of the cases, methods are developed and evaluated assuming perfect word segmentation. In this paper, we propose an experimental framework to quantify the goodness that word segmentation has on the performance achieved by word spotting methods in identical unbiased conditions. The framework consists of generating systematic distortions on segmentation and retrieving the original queries from the distorted dataset. We have tested our framework on several established and state-of-the-art methods using George Washington and Barcelona Marriage Datasets. The experiments done allow for an estimate of the end-to-end performance of word spotting methods.

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Titel: Evaluation of word spotting under improper segmentation scenario
verfasst von: Sounak Dey
Anguelos Nicolaou
Josep Lladós
Umapada Pal
Publikationsdatum: 01.08.2019
Verlag: Springer Berlin Heidelberg
Erschienen in: International Journal on Document Analysis and Recognition (IJDAR) / Ausgabe 4/2019
Print ISSN: 1433-2833
Elektronische ISSN: 1433-2825
DOI: https://doi.org/10.1007/s10032-019-00338-9

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