A Novel Approach for Foreign Substances Detection in Injection Using Clustering and Frame Difference
| Autor: | Yao Yu, Guiliang Lu, Yu Zhou, Sidan Du |
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| Rok vydání: | 2011 |
| Předmět: |
Computer science
Machine vision lcsh:Chemical technology Biochemistry Article computer vision Injections Analytical Chemistry detection of foreign substances Image Processing Computer-Assisted Cluster Analysis lcsh:TP1-1185 Computer vision Electrical and Electronic Engineering Cluster analysis Instrumentation Frame difference business.industry Motion detection Object (computer science) Atomic and Molecular Physics and Optics frame difference Artificial intelligence Artifacts business Algorithms clustering |
| Zdroj: | Sensors Volume 11 Issue 10 Pages 9121-9135 Sensors, Vol 11, Iss 10, Pp 9121-9135 (2011) Sensors (Basel, Switzerland) |
| ISSN: | 1424-8220 |
| DOI: | 10.3390/s111009121 |
| Popis: | This paper focuses on developing a novel technique based on machine vision for detection of foreign substances in injections. Mechanical control yields spin/stop movement of injections which helps to cause relative movement between foreign substances in liquid and an ampoule bottle. Foreign substances are classified into two categories: subsiding-slowly object and subsiding-fast object. A sequence of frames are captured by a camera and used to recognize foreign substances. After image preprocessing like noise reduction and motion detection, two different methods, Moving-object Clustering (MC) and Frame Difference, are proposed to detect the two categories respectively. MC is operated to cluster subsiding-slowly foreign substances, based on the invariant features of those objects. Frame Difference is defined to calculate the difference between two frames due to the change of subsiding-fast objects. 200 ampoule samples filled with injection are tested and the experimental result indicates that the approach can detect the visible foreign substances effectively. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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