The performance of KIMS in image recognition tasks

Celestine A. Ntuen, Eui H. Park, Young H. Park, Jung H. Kim, Kwang H. Sohn

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

KIMS is an acronym for a Knowledge-Based Image Management System developed in the Robotics and Artificial Intelligence Laboratory (RAIL) at North Carolina A&T State University. KIMS model architecture consists of rules which are developed through statistical experimentation with thresholding and quality control chart algorithms. The control architecture of KIMS is driven by the pattern of these rules. KIMS can analyze features of an X-ray image of a manufactured product such as printed circuit board in a real-time mode and make decisions on whether there are defect symptoms in the product. In this paper we present the current performance of KIMS in product inspection decision.

Original languageEnglish
Pages (from-to)244-248
Number of pages5
JournalComputers and Industrial Engineering
Volume19
Issue number1-4
DOIs
Publication statusPublished - 1990

    Fingerprint

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Engineering(all)

Cite this