Automated detection of Karnal bunt teliospores Metadata

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Title

  • Main Title Automated detection of Karnal bunt teliospores

Creator

  • Author: Linder, K. D.
    Creator Type: Personal
  • Author: Baumgart, C.
    Creator Type: Personal
  • Author: Creager, J.
    Creator Type: Personal
  • Author: Heinen, B.
    Creator Type: Personal
  • Author: Troupe, T.
    Creator Type: Personal
  • Author: Meyer, D.
    Creator Type: Personal
  • Author: Carr, J.
    Creator Type: Personal
  • Author: Quint, J.
    Creator Type: Personal

Contributor

  • Sponsor: United States. Department of Energy.
    Contributor Type: Organization
    Contributor Info: USDOE, Washington, DC (United States)

Publisher

  • Name: Allied-Signal Aerospace Company
    Place of Publication: Kansas City, Missouri
    Additional Info: Allied-Signal Aerospace Co., Kansas City, MO (United States). Kansas City Div.

Date

  • Creation: 1998-02-01

Language

  • English

Description

  • Content Description: Karnal bunt is a fungal disease which infects wheat and, when present in wheat crops, yields it unsatisfactory for human consumption. Due to the fact that Karnal bunt (KB) is difficult to detect in the field, samples are taken to laboratories where technicians use microscopes and methodically search for KB teliospores. AlliedSignal Federal Manufacturing and Technologies (FM and T), working with the Kansas Department of Agriculture, created a system which utilizes pattern recognition, feature extraction, and neural networks to prototype an automated detection system for identifying KB teliospores. System hardware consists of a biological compound microscope, motorized stage, CCD camera, frame grabber, and a PC. Integration of the system hardware with custom software comprises the machine vision system. Fundamental processing steps involve capturing an image from the slide, while concurrently processing the previous image. Features extracted from the acquired imagery are then processed by a neural network classifier which has been trained to recognize spore-like objects. Images with spore-like objects are reviewed by trained technicians. Benefits of this system include: (1) reduction of the overall cycle-time; (2) utilization of technicians for intelligent decision making (vs. manual searching); (3) a regulatory standard which is quantifiable and repeatable; (4) guaranteed 100% coverage of the cover slip; and (5) significantly enhanced detection accuracy.
  • Physical Description: 11 p.

Subject

  • Keyword: Pattern Recognition
  • Keyword: Wheat
  • Keyword: Crops
  • Keyword: Fungi
  • Keyword: Fungal Diseases
  • STI Subject Categories: 55 Biology And Medicine, Basic Studies
  • Keyword: Diagnosis
  • Keyword: Identification Systems
  • Keyword: Neural Networks
  • Keyword: Image Processing

Source

  • Conference: BIOS `98: an international symposium on biomedical optics, San Jose, CA (United States), 24-30 Jan 1998

Collection

  • Name: Office of Scientific & Technical Information Technical Reports
    Code: OSTI

Institution

  • Name: UNT Libraries Government Documents Department
    Code: UNTGD

Resource Type

  • Article

Format

  • Text

Identifier

  • Other: DE98051893
  • Report No.: KCP--613-6034
  • Report No.: CONF-980117--
  • Grant Number: AC04-76DP00613
  • Office of Scientific & Technical Information Report Number: 584919
  • Archival Resource Key: ark:/67531/metadc698599

Note

  • Display Note: OSTI as DE98051893
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