Skip to main content

2018 | OriginalPaper | Buchkapitel

Source Classification Using Document Images from Smartphones and Flatbed Scanners

verfasst von : Sharad Joshi, Gaurav Gupta, Nitin Khanna

Erschienen in: Computer Vision, Pattern Recognition, Image Processing, and Graphics

Verlag: Springer Singapore

Aktivieren Sie unsere intelligente Suche um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

With technological advancements, digital scans of printed documents are increasingly used in many systems in place of the original hard copy documents. This convenience to use digital scans comes at increased risk of potentially fraudulent and criminal activities due to their easy manipulation. To curb such activities, identification of source corresponding to a scanned document can provide important clues to investigating agencies and also help build a secure communication system. This work utilizes local tetra patterns to capture unique device-specific signatures from images of printed documents. In this first of its kind work for scanner identification, the method uses all characters to train a single classifier thereby, reducing the amount of training data required. The proposed method depicts font size independence when tested on an existing scanner dataset and a novel step towards font shape independence when tested on a smart phone dataset of comparable size (Supplementary material and code is available at https://​sites.​google.​com/​view/​manaslab).

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat Abramova, S., Bohme, R.: Detecting copy-move forgeries in scanned text documents. Electron. Imag. 8, 1–9 (2016) Abramova, S., Bohme, R.: Detecting copy-move forgeries in scanned text documents. Electron. Imag. 8, 1–9 (2016)
2.
Zurück zum Zitat Amerini, I., Caldelli, R., Del Bimbo, A., Di Fuccia, A., Saravo, L., Rizzo, A.P.: Copy-move forgery detection from printed images. In: IS&T/SPIE Electronic Imaging, p. 90280Y (2014) Amerini, I., Caldelli, R., Del Bimbo, A., Di Fuccia, A., Saravo, L., Rizzo, A.P.: Copy-move forgery detection from printed images. In: IS&T/SPIE Electronic Imaging, p. 90280Y (2014)
3.
Zurück zum Zitat Chiang, P.J., Khanna, N., Mikkilineni, A.K., Segovia, M.V.O., Suh, S., Allebach, J.P., Chiu, G.T.C., Delp, E.J.: Printer and scanner forensics. IEEE Signal Process. Mag. 26(2), 72–83 (2009)CrossRef Chiang, P.J., Khanna, N., Mikkilineni, A.K., Segovia, M.V.O., Suh, S., Allebach, J.P., Chiu, G.T.C., Delp, E.J.: Printer and scanner forensics. IEEE Signal Process. Mag. 26(2), 72–83 (2009)CrossRef
4.
Zurück zum Zitat Choi, C.H., Lee, M.J., Lee, H.K.: Scanner identification using spectral noise in the frequency domain. In: 17th IEEE International Conference on Image Processing, ICIP, pp. 2121–2124 (2010) Choi, C.H., Lee, M.J., Lee, H.K.: Scanner identification using spectral noise in the frequency domain. In: 17th IEEE International Conference on Image Processing, ICIP, pp. 2121–2124 (2010)
5.
Zurück zum Zitat Elsharkawy, Z., Abdelwahab, S., Dessouky, M., Elaraby, S., El-Samie, F.: Identifying unique flatbed scanner characteristics for matching a scanned image to its source. In: 30th IEEE National Radio Science Conference, NRSC, pp. 298–305 (2013) Elsharkawy, Z., Abdelwahab, S., Dessouky, M., Elaraby, S., El-Samie, F.: Identifying unique flatbed scanner characteristics for matching a scanned image to its source. In: 30th IEEE National Radio Science Conference, NRSC, pp. 298–305 (2013)
6.
Zurück zum Zitat Gloe, T., Franz, E., Winkler, A.: Forensics for flatbed scanners. In: Proceedings of SPIE Security, Steganography, and Watermarking of Multimedia Contents IX, p. 65051I (2007) Gloe, T., Franz, E., Winkler, A.: Forensics for flatbed scanners. In: Proceedings of SPIE Security, Steganography, and Watermarking of Multimedia Contents IX, p. 65051I (2007)
7.
Zurück zum Zitat Gou, H., Swaminathan, A., Wu, M.: Intrinsic sensor noise features for forensic analysis on scanners and scanned images. IEEE Trans. Inf. Forensics Secur. 4(3), 476–491 (2009)CrossRef Gou, H., Swaminathan, A., Wu, M.: Intrinsic sensor noise features for forensic analysis on scanners and scanned images. IEEE Trans. Inf. Forensics Secur. 4(3), 476–491 (2009)CrossRef
8.
Zurück zum Zitat Joshi, S., Khanna, N.: Single classifier-based passive system for source printer classification using local texture features. arXiv preprint arXiv:1706.07422 (2017) Joshi, S., Khanna, N.: Single classifier-based passive system for source printer classification using local texture features. arXiv preprint arXiv:​1706.​07422 (2017)
9.
Zurück zum Zitat Khanna, N., Delp, E.J.: Intrinsic signatures for scanned documents forensics: effect of font shape and size. In: Proceedings of IEEE International Symposium on Circuits and Systems, ISCAS, pp. 3060–3063 (2010) Khanna, N., Delp, E.J.: Intrinsic signatures for scanned documents forensics: effect of font shape and size. In: Proceedings of IEEE International Symposium on Circuits and Systems, ISCAS, pp. 3060–3063 (2010)
10.
Zurück zum Zitat Khanna, N., Mikkilineni, A.K., Delp, E.J.: Scanner identification using feature-based processing and analysis. IEEE Trans. Inf. Forensics Secur. 4(1), 123–139 (2009)CrossRef Khanna, N., Mikkilineni, A.K., Delp, E.J.: Scanner identification using feature-based processing and analysis. IEEE Trans. Inf. Forensics Secur. 4(1), 123–139 (2009)CrossRef
11.
Zurück zum Zitat Murala, S., Maheshwari, R., Balasubramanian, R.: Local tetra patterns: a new feature descriptor for content-based image retrieval. IEEE Trans. Image Process. 21(5), 2874–2886 (2012)MathSciNetCrossRef Murala, S., Maheshwari, R., Balasubramanian, R.: Local tetra patterns: a new feature descriptor for content-based image retrieval. IEEE Trans. Image Process. 21(5), 2874–2886 (2012)MathSciNetCrossRef
12.
Zurück zum Zitat Ojala, T., Pietikäinen, M., Mäenpää, M.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans. Pattern Anal. Mach. Intell. 24(7), 971–987 (2002)CrossRef Ojala, T., Pietikäinen, M., Mäenpää, M.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans. Pattern Anal. Mach. Intell. 24(7), 971–987 (2002)CrossRef
14.
Zurück zum Zitat Sugawara, S.: Identification of scanner models by comparison of scanned hologram images. Forensic Sci. Int. 241, 69–83 (2014)CrossRef Sugawara, S.: Identification of scanner models by comparison of scanned hologram images. Forensic Sci. Int. 241, 69–83 (2014)CrossRef
15.
Zurück zum Zitat Tan, X., Triggs, B.: Enhanced local texture feature sets for face recognition under difficult lighting conditions. IEEE Trans. Image Process. 19(6), 1635–1650 (2010)MathSciNetCrossRef Tan, X., Triggs, B.: Enhanced local texture feature sets for face recognition under difficult lighting conditions. IEEE Trans. Image Process. 19(6), 1635–1650 (2010)MathSciNetCrossRef
16.
Zurück zum Zitat Xu, G., Shi, Y.Q.: Camera model identification using local binary patterns. In: IEEE International Conference on Multimedia and Expo, ICME, pp. 392–397 (2012) Xu, G., Shi, Y.Q.: Camera model identification using local binary patterns. In: IEEE International Conference on Multimedia and Expo, ICME, pp. 392–397 (2012)
17.
Zurück zum Zitat Zhang, B., Gao, Y., Zhao, S., Liu, J.: Local derivative pattern versus local binary pattern: face recognition with high-order local pattern descriptor. IEEE Trans. Image Process. 19(2), 533–544 (2010)MathSciNetCrossRef Zhang, B., Gao, Y., Zhao, S., Liu, J.: Local derivative pattern versus local binary pattern: face recognition with high-order local pattern descriptor. IEEE Trans. Image Process. 19(2), 533–544 (2010)MathSciNetCrossRef
Metadaten
Titel
Source Classification Using Document Images from Smartphones and Flatbed Scanners
verfasst von
Sharad Joshi
Gaurav Gupta
Nitin Khanna
Copyright-Jahr
2018
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-13-0020-2_25