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Neural classifier for micro work piece recognition
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DOI：10.1016/j.imavis.2006.02.006.png)
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Abstract
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The aim of this article, is to describe a technical vision system for automation of micromanufacturing and microassembly processes. One of the principal problems is connected with the recognition of work pieces and detection of their positions. For this purpose we use neural classifier named limited receptive area (LIRA) grey scale. This classifier was developed for wide range of image recognition tasks. A special software was designed. We describe some experiments and results of application of LIRA in the recognition of micro work pieces and their positions for automated handling system. The best recognition rate obtained was 94%. (c) 2006 Elsevier B.V. All rights reserved.
Keywords:
neural network
neural classifier
technical vision
object recognition
position recognition
microassembly
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