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JOURNALS // Problemy Upravleniya // Archive

Probl. Upr., 2007 Issue 4, Pages 36–42 (Mi pu259)

This article is cited in 1 paper

Information technologies controls

Cluster analysis application to automatic flaw detection

I. L. Vasilieva, D. N. Sidorovb

a Institute of System Dynamics and Control Theory, Siberian Branch of the Russian Academy of Sciences
b L. A. Melentiev Energy Systems Institute, Siberian Branch of the Russian Academy of Sciences

Abstract: The problem of automatic detection and categorization of flaws that arises in machine vision system development is discussed. A method of its solution is proposed. At the first stage, an autonomous process of system learning is performed where the learning samples of the analyzed flaw symptoms are split into clusters with medians. At the second stage, the real-time inspection process is performed where each incoming pattern is categorized according to the nearest median type. The paper notes that the comparative analysis against other techniques showed the effectiveness of the method proposed.

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