Hyperspectral imaging for ink mismatch detection

Zohaib Khan, Faisal Shafait, Ajmal Mian

    Research output: Chapter in Book/Conference paperConference paper

    23 Citations (Scopus)

    Abstract

    Ink mismatch detection provides important clues to forensic document examiners by identifying whether a particular handwritten note was written with a specific pen, or to show that some part (e.g. signature) of a note is written with a different ink as compared to the rest of the note. In this paper, we show that a hyper spectral image (HSI) of handwritten notes can discriminate between inks that are visually similar in appearance. For this purpose, we develop the first ever hyper spectral image database of handwritten notes in various blue and black inks, comprising a total of 70 hyper spectral images each in 33 bands of the visible spectrum. In an unsupervised clustering scheme, the spectral responses of inks fall into separate clusters to allow segmentation of two different inks in a questioned document. The same method fails to segment inks correctly when applied to RGB scans of these documents, since the inks are very hard to distinguish in the visible spectral range. HSI overcomes the shortcomings of RGB and allows better discrimination between inks. We further evaluate which subset of bands from HSI is most useful for the purpose of ink mismatch detection. We hope that these findings will stimulate the use of HSI in document analysis research, especially for questioned document examination.
    Original languageEnglish
    Title of host publicationProceedings of the International Conference on Document Analysis and Recognition, ICDAR
    Place of PublicationUSA
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    Pages877-881
    ISBN (Print)15205363
    DOIs
    Publication statusPublished - 2013
    Event12th International Conference on Document Analysis and Recognition, ICDAR 2013 - Washington, United States
    Duration: 25 Aug 201328 Aug 2013

    Conference

    Conference12th International Conference on Document Analysis and Recognition, ICDAR 2013
    CountryUnited States
    CityWashington
    Period25/08/1328/08/13

    Fingerprint

    detection
    ink
    visible spectrum
    segmentation
    document
    method
    analysis

    Cite this

    Khan, Z., Shafait, F., & Mian, A. (2013). Hyperspectral imaging for ink mismatch detection. In Proceedings of the International Conference on Document Analysis and Recognition, ICDAR (pp. 877-881). USA: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICDAR.2013.179
    Khan, Zohaib ; Shafait, Faisal ; Mian, Ajmal. / Hyperspectral imaging for ink mismatch detection. Proceedings of the International Conference on Document Analysis and Recognition, ICDAR. USA : IEEE, Institute of Electrical and Electronics Engineers, 2013. pp. 877-881
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    title = "Hyperspectral imaging for ink mismatch detection",
    abstract = "Ink mismatch detection provides important clues to forensic document examiners by identifying whether a particular handwritten note was written with a specific pen, or to show that some part (e.g. signature) of a note is written with a different ink as compared to the rest of the note. In this paper, we show that a hyper spectral image (HSI) of handwritten notes can discriminate between inks that are visually similar in appearance. For this purpose, we develop the first ever hyper spectral image database of handwritten notes in various blue and black inks, comprising a total of 70 hyper spectral images each in 33 bands of the visible spectrum. In an unsupervised clustering scheme, the spectral responses of inks fall into separate clusters to allow segmentation of two different inks in a questioned document. The same method fails to segment inks correctly when applied to RGB scans of these documents, since the inks are very hard to distinguish in the visible spectral range. HSI overcomes the shortcomings of RGB and allows better discrimination between inks. We further evaluate which subset of bands from HSI is most useful for the purpose of ink mismatch detection. We hope that these findings will stimulate the use of HSI in document analysis research, especially for questioned document examination.",
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    Khan, Z, Shafait, F & Mian, A 2013, Hyperspectral imaging for ink mismatch detection. in Proceedings of the International Conference on Document Analysis and Recognition, ICDAR. IEEE, Institute of Electrical and Electronics Engineers, USA, pp. 877-881, 12th International Conference on Document Analysis and Recognition, ICDAR 2013, Washington, United States, 25/08/13. https://doi.org/10.1109/ICDAR.2013.179

    Hyperspectral imaging for ink mismatch detection. / Khan, Zohaib; Shafait, Faisal; Mian, Ajmal.

    Proceedings of the International Conference on Document Analysis and Recognition, ICDAR. USA : IEEE, Institute of Electrical and Electronics Engineers, 2013. p. 877-881.

    Research output: Chapter in Book/Conference paperConference paper

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    AB - Ink mismatch detection provides important clues to forensic document examiners by identifying whether a particular handwritten note was written with a specific pen, or to show that some part (e.g. signature) of a note is written with a different ink as compared to the rest of the note. In this paper, we show that a hyper spectral image (HSI) of handwritten notes can discriminate between inks that are visually similar in appearance. For this purpose, we develop the first ever hyper spectral image database of handwritten notes in various blue and black inks, comprising a total of 70 hyper spectral images each in 33 bands of the visible spectrum. In an unsupervised clustering scheme, the spectral responses of inks fall into separate clusters to allow segmentation of two different inks in a questioned document. The same method fails to segment inks correctly when applied to RGB scans of these documents, since the inks are very hard to distinguish in the visible spectral range. HSI overcomes the shortcomings of RGB and allows better discrimination between inks. We further evaluate which subset of bands from HSI is most useful for the purpose of ink mismatch detection. We hope that these findings will stimulate the use of HSI in document analysis research, especially for questioned document examination.

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    Khan Z, Shafait F, Mian A. Hyperspectral imaging for ink mismatch detection. In Proceedings of the International Conference on Document Analysis and Recognition, ICDAR. USA: IEEE, Institute of Electrical and Electronics Engineers. 2013. p. 877-881 https://doi.org/10.1109/ICDAR.2013.179