The potential of using log biometrics to track sawmill flow Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/nc580q40b

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  • We studied the feasibility of using end-grain characteristics to match individual boards and cants back to their parent Douglas-fir (Pseudotsuga menziesii) logs. After reviewing marking/reading and biometric automated identification systems, we focused on end-grain biometrics because they appear to have the most promise for sawmills. Biometric identification requires that every individual be unique in some quantifiable way and that the trait used remain relatively unchanged over time. To determine whether end-grain characteristics could meet these requirements, we imaged 120 Douglas-fir cross-sections three times over the span of three days. An image matching algorithm matched images cropped to simulate cants and boards to cross-section images taken at an earlier time. We analyzed the results using standard receiver operating characteristic curves commonly used to evaluate biometric identification systems. Results showed that 98% of the day 2 board images were correctly matched back to their day 1 parent cant images, and 93% for the day 3 to the day 2 images. When cants were matched to uncropped rounds, 88% of the day 2 images were correctly matched to the day 1 images, and 83% for the day 3 to day 2 images. The results are encouraging because they suggest that individual logs can be identified using the variability of end-grain characteristics.
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  • description.provenance : Approved for entry into archive by Laura Wilson(laura.wilson@oregonstate.edu) on 2010-01-21T00:13:19Z (GMT) No. of bitstreams: 1 The potential of log biometrics to track sawmill flow.pdf: 1587945 bytes, checksum: 8a44c811f0daf398dc649468df992002 (MD5)
  • description.provenance : Submitted by Matthew Peterson (petermat@onid.orst.edu) on 2010-01-14T17:47:55Z No. of bitstreams: 1 The potential of log biometrics to track sawmill flow.pdf: 1587945 bytes, checksum: 8a44c811f0daf398dc649468df992002 (MD5)
  • description.provenance : Made available in DSpace on 2010-01-21T00:13:19Z (GMT). No. of bitstreams: 1 The potential of log biometrics to track sawmill flow.pdf: 1587945 bytes, checksum: 8a44c811f0daf398dc649468df992002 (MD5)
  • description.provenance : Approved for entry into archive by Julie Kurtz(julie.kurtz@oregonstate.edu) on 2010-01-18T18:39:58Z (GMT) No. of bitstreams: 1 The potential of log biometrics to track sawmill flow.pdf: 1587945 bytes, checksum: 8a44c811f0daf398dc649468df992002 (MD5)

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