Classification of pistachio nuts using a string matching technique

A. Ghazanfari, J. Irudayaraj

Research output: Contribution to journalArticlepeer-review

Abstract

A modified cyclic string matching algorithm was developed and applied to classify four classes of pistachio nuts, based on their two- dimensional shapes. In this method, a pistachio nut was represented by a string consisting of N angularly equispaced radii extending from the centroid to the boundary. An algorithm was also developed for determining a prototype for each class. The recognition algorithm, based on a string matching technique, calculated the cumulative distance between an unknown and a class prototype. The class of the unknown was determined by the minimum- distance classification rule. The developed algorithm gave an overall accuracy of 90%. This procedure could be extended to classify other agricultural materials.

Original languageEnglish (US)
Pages (from-to)1197-1202
Number of pages6
JournalTransactions of the American Society of Agricultural Engineers
Volume39
Issue number3
StatePublished - Sep 14 1996
Externally publishedYes

Keywords

  • Boundary sequences
  • Classification
  • Image analysis
  • Pistachio
  • String matching

ASJC Scopus subject areas

  • Agricultural and Biological Sciences (miscellaneous)

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