A combined Harris-SIFT approach for indexing the Arabic document

Youssef Elfakir; Ghizlane Khaissidi; Mostafa Mrabti; Driss Chenouni; Mounim El Yacoubi

doi:10.1109/SSD.2017.8166995

A combined Harris-SIFT approach for indexing the Arabic document

Youssef Elfakir, Ghizlane Khaissidi, Mostafa Mrabti, Driss Chenouni, Mounim El Yacoubi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper present a query-by-example word spotting in handwritten Arabic documents, based on Harris detector and Scale Invariant Feature Transform (SIFT), without using any text word or line segmentation approach, because any errors affect to the subsequent word representations. First, the interest points are automatically extracted from the images using Harris detector, then, we use SIFT descriptor to represent each interest point in the images. In the end, we represent the image's regions as histogram by using bag of visual words method. The validate study is conducted under a series of controlled experiments on handwritten Arabic documents images.

Original language	English
Title of host publication	2017 14th International Multi-Conference on Systems, Signals and Devices, SSD 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	621-624
Number of pages	4
ISBN (Electronic)	9781538631751
DOIs	https://doi.org/10.1109/SSD.2017.8166995
Publication status	Published - 4 Dec 2017
Externally published	Yes
Event	14th International Multi-Conference on Systems, Signals and Devices, SSD 2017 - Marrakech, Morocco Duration: 28 Mar 2017 → 31 Mar 2017

Publication series

Name	2017 14th International Multi-Conference on Systems, Signals and Devices, SSD 2017
Volume	2017-January

Conference

Conference	14th International Multi-Conference on Systems, Signals and Devices, SSD 2017
Country/Territory	Morocco
City	Marrakech
Period	28/03/17 → 31/03/17

Keywords

Bag-of-visual-word
Harris detector
Scale-invariant feature transform
Word spotting
handwritten Arabic document

Access to Document

10.1109/SSD.2017.8166995

Cite this

Elfakir, Y., Khaissidi, G., Mrabti, M., Chenouni, D., & El Yacoubi, M. (2017). A combined Harris-SIFT approach for indexing the Arabic document. In 2017 14th International Multi-Conference on Systems, Signals and Devices, SSD 2017 (pp. 621-624). (2017 14th International Multi-Conference on Systems, Signals and Devices, SSD 2017; Vol. 2017-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SSD.2017.8166995

Elfakir, Youssef ; Khaissidi, Ghizlane ; Mrabti, Mostafa et al. / A combined Harris-SIFT approach for indexing the Arabic document. 2017 14th International Multi-Conference on Systems, Signals and Devices, SSD 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 621-624 (2017 14th International Multi-Conference on Systems, Signals and Devices, SSD 2017).

@inproceedings{d9a741fef6df401a932e4df99c39c8ee,

title = "A combined Harris-SIFT approach for indexing the Arabic document",

abstract = "This paper present a query-by-example word spotting in handwritten Arabic documents, based on Harris detector and Scale Invariant Feature Transform (SIFT), without using any text word or line segmentation approach, because any errors affect to the subsequent word representations. First, the interest points are automatically extracted from the images using Harris detector, then, we use SIFT descriptor to represent each interest point in the images. In the end, we represent the image's regions as histogram by using bag of visual words method. The validate study is conducted under a series of controlled experiments on handwritten Arabic documents images.",

keywords = "Bag-of-visual-word, Harris detector, Scale-invariant feature transform, Word spotting, handwritten Arabic document",

author = "Youssef Elfakir and Ghizlane Khaissidi and Mostafa Mrabti and Driss Chenouni and \{El Yacoubi\}, Mounim",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 14th International Multi-Conference on Systems, Signals and Devices, SSD 2017 ; Conference date: 28-03-2017 Through 31-03-2017",

year = "2017",

month = dec,

day = "4",

doi = "10.1109/SSD.2017.8166995",

language = "English",

series = "2017 14th International Multi-Conference on Systems, Signals and Devices, SSD 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "621--624",

booktitle = "2017 14th International Multi-Conference on Systems, Signals and Devices, SSD 2017",

}

Elfakir, Y, Khaissidi, G, Mrabti, M, Chenouni, D & El Yacoubi, M 2017, A combined Harris-SIFT approach for indexing the Arabic document. in 2017 14th International Multi-Conference on Systems, Signals and Devices, SSD 2017. 2017 14th International Multi-Conference on Systems, Signals and Devices, SSD 2017, vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 621-624, 14th International Multi-Conference on Systems, Signals and Devices, SSD 2017, Marrakech, Morocco, 28/03/17. https://doi.org/10.1109/SSD.2017.8166995

A combined Harris-SIFT approach for indexing the Arabic document. / Elfakir, Youssef; Khaissidi, Ghizlane; Mrabti, Mostafa et al.
2017 14th International Multi-Conference on Systems, Signals and Devices, SSD 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 621-624 (2017 14th International Multi-Conference on Systems, Signals and Devices, SSD 2017; Vol. 2017-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - El Yacoubi, Mounim

PY - 2017/12/4

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N2 - This paper present a query-by-example word spotting in handwritten Arabic documents, based on Harris detector and Scale Invariant Feature Transform (SIFT), without using any text word or line segmentation approach, because any errors affect to the subsequent word representations. First, the interest points are automatically extracted from the images using Harris detector, then, we use SIFT descriptor to represent each interest point in the images. In the end, we represent the image's regions as histogram by using bag of visual words method. The validate study is conducted under a series of controlled experiments on handwritten Arabic documents images.

AB - This paper present a query-by-example word spotting in handwritten Arabic documents, based on Harris detector and Scale Invariant Feature Transform (SIFT), without using any text word or line segmentation approach, because any errors affect to the subsequent word representations. First, the interest points are automatically extracted from the images using Harris detector, then, we use SIFT descriptor to represent each interest point in the images. In the end, we represent the image's regions as histogram by using bag of visual words method. The validate study is conducted under a series of controlled experiments on handwritten Arabic documents images.

KW - Bag-of-visual-word

KW - Harris detector

KW - Scale-invariant feature transform

KW - Word spotting

KW - handwritten Arabic document

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Elfakir Y, Khaissidi G, Mrabti M, Chenouni D, El Yacoubi M. A combined Harris-SIFT approach for indexing the Arabic document. In 2017 14th International Multi-Conference on Systems, Signals and Devices, SSD 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 621-624. (2017 14th International Multi-Conference on Systems, Signals and Devices, SSD 2017). doi: 10.1109/SSD.2017.8166995

A combined Harris-SIFT approach for indexing the Arabic document

Abstract

Publication series

Conference

Keywords

Access to Document

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Cite this