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Sensors 2009, 9(5), 3386-3404; doi:10.3390/s90503386

Intelligent Foreign Particle Inspection Machine for Injection Liquid Examination Based on Modified Pulse-Coupled Neural Networks

College of Electrical and Information Engineering, Hunan University, China
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Received: 25 March 2009 / Revised: 22 April 2009 / Accepted: 23 April 2009 / Published: 7 May 2009
(This article belongs to the Section Chemical Sensors)

Abstract

A biologically inspired spiking neural network model, called pulse-coupled neural networks (PCNN), has been applied in an automatic inspection machine to detect visible foreign particles intermingled in glucose or sodium chloride injection liquids. Proper mechanisms and improved spin/stop techniques are proposed to avoid the appearance of air bubbles, which increases the algorithms’ complexity. Modified PCNN is adopted to segment the difference images, judging the existence of foreign particles according to the continuity and smoothness properties of their moving traces. Preliminarily experimental results indicate that the inspection machine can detect the visible foreign particles effectively and the detection speed, accuracy and correct detection rate also satisfying the needs of medicine preparation. View Full-Text
Keywords: Intelligent inspection machine; foreign particle detection; modified PCNN; injection quality inspection; image processing; illumination styles Intelligent inspection machine; foreign particle detection; modified PCNN; injection quality inspection; image processing; illumination styles
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Ge, J.; Wang, Y.; Zhou, B.; Zhang, H. Intelligent Foreign Particle Inspection Machine for Injection Liquid Examination Based on Modified Pulse-Coupled Neural Networks. Sensors 2009, 9, 3386-3404.

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