Volume 42, Issue 5 (September 1997)

    Writer Identification by Professional Document Examiners

    (Received 29 October 1996; accepted 10 January 1997)


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    Reliable data on the capabilities of professional document examiners are scarce, rendering most past characterizations of these capabilities somewhat speculative. We report on a comprehensive test administered to more than 100 professional document examiners, intended to close this data gap in the area of writer identification. Each examiner made 144 pair-wise comparisons of freely-created original handwritten documents. The task was to determine whether or not a “match” was detected, namely whether or not the two documents were written by the same hand. Matching criteria were based on the identification and strong probability definitions of the ASTM standard E1658. The professionals were tested in three groups (in the northeastern, southeastern, and southwestern United States). In addition, we have created a control group of similar educational background. Several individuals training to become professional document examiners were tested as well.

    Examination of the data and statistical tests show that the answers collected from the professional and nonprofessional groups came from different populations. The trainees' data were shown to have come from a population that is distinct from both professional and nonprofessional groups. Unlike the professional examiners, the nonprofessionals tended to grossly over-associate. They erroneously “matched” many documents that were created by different writers, mismatching almost six times as many unknown documents to database documents as the professionals did (38.3% vs. 6.5% of the documents). The results of our test lay to rest the debate over whether or not professional document examiners possess writer-identification skills absent in the general population. They do.

    Author Information:

    Fielding, G
    Data Fusion Laboratory, Electrical and Computer Engineering Department, Drexel University, Philadelphia, PA

    Kam, M
    Data Fusion Laboratory, Electrical and Computer Engineering Department, Drexel University, Philadelphia, PA

    Conn, R
    Applied Physics Laboratory, The Johns Hopkins University, Baltimore, MD

    Stock #: JFS14207J

    ISSN: 0022-1198

    DOI: 10.1520/JFS14207J

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    Title Writer Identification by Professional Document Examiners
    Symposium , 0000-00-00
    Committee E30