Initiating GrabCut by Color Difference for Automatic Foreground Extraction of Passport Imagery

Adriá Arbués Sangüesa; Nicolai Krogh Jørgensen; Christian Aagaard Larsen; Kamal Nasrollahi; Thomas B. Moeslund

doi:10.1109/IPTA.2016.7820964

Initiating GrabCut by Color Difference for Automatic Foreground Extraction of Passport Imagery

Adriá Arbués Sangüesa, Nicolai Krogh Jørgensen, Christian Aagaard Larsen, Kamal Nasrollahi, Thomas B. Moeslund

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

2 Citations (Scopus)

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Abstract

Grabcut, an iterative algorithm based on Graph Cut, is a popular foreground segmentation method. However, it suffers from a main drawback: a manual interaction is required in order to start segmenting the image. In this paper, four different methods based on image pairs are used to obtain an initial extraction of the foreground. Then, the obtained initial estimation of the foreground is used as input to the GrabCut algorithm, thus avoiding the need of interaction. Moreover, this paper is focused on passport images, which require an almost pixel-perfect segmentation in order to be a valid photo. Having gathered our own dataset and generated ground truth images, promising results are obtained in terms of F1-scores, with a maximum mean of 0.975 among all the images, improving the performance of GrabCut in all cases. Some future work directions are given for those unsolved issues that were faced, such as the segmentation in hair regions or tests in a non-uniform background scenario.

Original language	English
Title of host publication	IEEE International Conference on Image Processing Theory, Tools and Applications
Publisher	IEEE
Publication date	Dec 2016
ISBN (Print)	978-1-4673-8911-2
ISBN (Electronic)	978-1-4673-8910-5
DOIs	https://doi.org/10.1109/IPTA.2016.7820964
Publication status	Published - Dec 2016
Event	IEEE International Conference on Image Processing Theory, Tools and Applications - Oulu, Finland Duration: 12 Dec 2016 → 15 Dec 2016 Conference number: 6 http://www.ipta-conference.com/ipta16/

Conference

Conference	IEEE International Conference on Image Processing Theory, Tools and Applications
Number	6
Country/Territory	Finland
City	Oulu
Period	12/12/2016 → 15/12/2016
Internet address	http://www.ipta-conference.com/ipta16/

Keywords

Foreground Extraction
Image Pairs
GrabCut
Passport Imagery
Color Difference

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@inproceedings{67e3f1d0530a4a56a41400ffd2edd8e7,

title = "Initiating GrabCut by Color Difference for Automatic Foreground Extraction of Passport Imagery",

abstract = "Grabcut, an iterative algorithm based on Graph Cut, is a popular foreground segmentation method. However, it suffers from a main drawback: a manual interaction is required in order to start segmenting the image. In this paper, four different methods based on image pairs are used to obtain an initial extraction of the foreground. Then, the obtained initial estimation of the foreground is used as input to the GrabCut algorithm, thus avoiding the need of interaction. Moreover, this paper is focused on passport images, which require an almost pixel-perfect segmentation in order to be a valid photo. Having gathered our own dataset and generated ground truth images, promising results are obtained in terms of F1-scores, with a maximum mean of 0.975 among all the images, improving the performance of GrabCut in all cases. Some future work directions are given for those unsolved issues that were faced, such as the segmentation in hair regions or tests in a non-uniform background scenario.",

keywords = "Foreground Extraction, Image Pairs, GrabCut, Passport Imagery, Color Difference",

author = "Sang{\"u}esa, {Adri{\'a} Arbu{\'e}s} and J{\o}rgensen, {Nicolai Krogh} and Larsen, {Christian Aagaard} and Kamal Nasrollahi and Moeslund, {Thomas B.}",

year = "2016",

month = dec,

doi = "10.1109/IPTA.2016.7820964",

language = "English",

isbn = "978-1-4673-8911-2",

booktitle = "IEEE International Conference on Image Processing Theory, Tools and Applications",

publisher = "IEEE",

address = "United States",

note = "IEEE International Conference on Image Processing Theory, Tools and Applications, IPTA ; Conference date: 12-12-2016 Through 15-12-2016",

url = "http://www.ipta-conference.com/ipta16/",

}

Sangüesa, AA, Jørgensen, NK, Larsen, CA, Nasrollahi, K & Moeslund, TB 2016, Initiating GrabCut by Color Difference for Automatic Foreground Extraction of Passport Imagery. in IEEE International Conference on Image Processing Theory, Tools and Applications. IEEE, IEEE International Conference on Image Processing Theory, Tools and Applications, Oulu, Finland, 12/12/2016. https://doi.org/10.1109/IPTA.2016.7820964

Initiating GrabCut by Color Difference for Automatic Foreground Extraction of Passport Imagery. / Sangüesa, Adriá Arbués; Jørgensen, Nicolai Krogh; Larsen, Christian Aagaard et al.
IEEE International Conference on Image Processing Theory, Tools and Applications. IEEE, 2016.

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

TY - GEN

T1 - Initiating GrabCut by Color Difference for Automatic Foreground Extraction of Passport Imagery

AU - Sangüesa, Adriá Arbués

AU - Jørgensen, Nicolai Krogh

AU - Larsen, Christian Aagaard

AU - Nasrollahi, Kamal

AU - Moeslund, Thomas B.

N1 - Conference code: 6

PY - 2016/12

Y1 - 2016/12

N2 - Grabcut, an iterative algorithm based on Graph Cut, is a popular foreground segmentation method. However, it suffers from a main drawback: a manual interaction is required in order to start segmenting the image. In this paper, four different methods based on image pairs are used to obtain an initial extraction of the foreground. Then, the obtained initial estimation of the foreground is used as input to the GrabCut algorithm, thus avoiding the need of interaction. Moreover, this paper is focused on passport images, which require an almost pixel-perfect segmentation in order to be a valid photo. Having gathered our own dataset and generated ground truth images, promising results are obtained in terms of F1-scores, with a maximum mean of 0.975 among all the images, improving the performance of GrabCut in all cases. Some future work directions are given for those unsolved issues that were faced, such as the segmentation in hair regions or tests in a non-uniform background scenario.

AB - Grabcut, an iterative algorithm based on Graph Cut, is a popular foreground segmentation method. However, it suffers from a main drawback: a manual interaction is required in order to start segmenting the image. In this paper, four different methods based on image pairs are used to obtain an initial extraction of the foreground. Then, the obtained initial estimation of the foreground is used as input to the GrabCut algorithm, thus avoiding the need of interaction. Moreover, this paper is focused on passport images, which require an almost pixel-perfect segmentation in order to be a valid photo. Having gathered our own dataset and generated ground truth images, promising results are obtained in terms of F1-scores, with a maximum mean of 0.975 among all the images, improving the performance of GrabCut in all cases. Some future work directions are given for those unsolved issues that were faced, such as the segmentation in hair regions or tests in a non-uniform background scenario.

KW - Foreground Extraction

KW - Image Pairs

KW - GrabCut

KW - Passport Imagery

KW - Color Difference

U2 - 10.1109/IPTA.2016.7820964

DO - 10.1109/IPTA.2016.7820964

M3 - Article in proceeding

SN - 978-1-4673-8911-2

BT - IEEE International Conference on Image Processing Theory, Tools and Applications

PB - IEEE

T2 - IEEE International Conference on Image Processing Theory, Tools and Applications

Y2 - 12 December 2016 through 15 December 2016

ER -

Initiating GrabCut by Color Difference for Automatic Foreground Extraction of Passport Imagery

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