Elsevier

Pattern Recognition

Volume 6, Issue 2, October 1974, Pages 97-103
Pattern Recognition

Automatic classification of grains via pattern recognition techniques

https://doi.org/10.1016/0031-3203(74)90012-0Get rights and content

Abstract

During production, storage and shipment, a crop of feed grain is often contaminated with admixtures of other grains or foreign material. Failure to meet the contractural limits of purity can result in monetary penalties or may prevent completion of the sales transaction. Presently, purity is established by human inspectors. They subject a carefully selected sample to 100 per cent visual inspection.

This paper describes part of the development of a high speed, automatic sorting and grading procedure. A recursive learning pattern classification scheme is described which yields an overall accuracy of about 98 per cent.

References (10)

  • A.R. Edison et al.

    Size measurement statistics of kernels of six grains

  • W.L. Brogan

    A recursive self-learning pattern classification technique

  • Annon. Determine the feasibility of using optical characteristics for identifying specific grains and foreign materials...
  • A.L. Hawk et al.

    Reflectance characteristics of various grains

  • L. Segerlind et al.

    Grain kernel identification by profile analysis

There are more references available in the full text version of this article.

Cited by (7)

View all citing articles on Scopus
View full text