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 proceedingArticle in proceedingResearchpeer-review

1 Citation (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 languageEnglish
Title of host publicationIEEE International Conference on Image Processing Theory, Tools and Applications
PublisherIEEE
Publication dateDec 2016
ISBN (Print)978-1-4673-8911-2
ISBN (Electronic)978-1-4673-8910-5
DOIs
Publication statusPublished - Dec 2016
EventIEEE International Conference on Image Processing Theory, Tools and Applications - Oulu, Finland
Duration: 12 Dec 201615 Dec 2016
Conference number: 6
http://www.ipta-conference.com/ipta16/

Conference

ConferenceIEEE International Conference on Image Processing Theory, Tools and Applications
Number6
CountryFinland
CityOulu
Period12/12/201615/12/2016
Internet address

Fingerprint

Color
Pixels

Keywords

  • Foreground Extraction
  • Image Pairs
  • GrabCut
  • Passport Imagery
  • Color Difference

Cite this

Sangüesa, A. A., Jørgensen, N. K., Larsen, C. A., Nasrollahi, K., & Moeslund, T. B. (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. https://doi.org/10.1109/IPTA.2016.7820964
Sangüesa, Adriá Arbués ; Jørgensen, Nicolai Krogh ; Larsen, Christian Aagaard ; Nasrollahi, Kamal ; Moeslund, Thomas B. / Initiating GrabCut by Color Difference for Automatic Foreground Extraction of Passport Imagery. IEEE International Conference on Image Processing Theory, Tools and Applications. IEEE, 2016.
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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; Nasrollahi, Kamal; Moeslund, Thomas B.

IEEE International Conference on Image Processing Theory, Tools and Applications. IEEE, 2016.

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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AU - Nasrollahi, Kamal

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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.

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