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Slap fingerprint segmentation evaluation 2004 analysis report / Bradford Ulery [and others].

Hicklin, R. Austin. (Added Author). Indovina, Michael. (Added Author). Kwong, Kayee. (Added Author). Ulery, Bradford. (Added Author). Watson, C. I.| (Craig I.) (Added Author). Mitretek Systems. (Added Author). National Institute of Standards and Technology (U.S.) (Added Author).
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Series Information

NISTIR ; 7209.

Record details

  • Physical Description: 1 online resource (8 pages) : illustrations.
  • Publisher: [Gaithersburg, MD] : U.S. Dept. of Commerce, National Institute of Standards and Technology, [2005]

Content descriptions

General Note:
"8 March 2005."
Contributed record: Metadata reviewed, not verified. Some fields updated by batch processes.
Title from page 1, viewed March 13, 2007.
Summary, etc.:
The Slap Fingerprint Segmentation Evaluation 2004 (SlapSeg04) was conducted to assess the accuracy of algorithms used to segment slap fingerprint images into individual fingerprint images. Thirteen slap segmentation applications from ten different organizations were evaluated using data from seven government sources. The source of data, the segmentation software used, and the scoring criteria used were each found to have a significant impact on accuracy. The most accurate segmenters produced at least three highly matchable fingers and correctly identified finger positions in from 93% to over 99% of the slap images, depending on the data source. The data source had a much greater effect on success rate than whether the images were collected using livescan devices or paper. Most segmenters achieved comparable accuracies on the better quality data, but there were significant differences among segmenters when processing poor quality data. Some segmenters are capable of identifying many, but not all, problem slaps: failure rates could be cut substantially by allowing some of the slaps to be recaptured or rejected.
Subject: Fingerprints > Identification > Automation.
Image processing > Testing.

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