Impurity Detection Using Machine Vision

Abstract:

In the fields of transparent liquid impurity detection based on machine vision technology, how to detect and identify a variety of impurities effectively in the liquid is a difficult problem which has not yet been solved, mainly in the low recognition rate, the slow recognition speed, and the phenomenon of error detection and undetected. Therefore, a new impurity detection method based on machine vision is presented in this paper. The experiments show that this method can decrease the recognition speed to 100ms for impurities’ diameter greater than 1mm and achieved a 99% recognition rate.

• Periodical: Advanced Materials Research (Volumes 468-471)
• Pages: 2057-2060
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.468-471.2057
• Online since: February 2012
• Authors: Bin Huang, Jian Feng Li, Jin Chen Wang, Yin Zhou He, Wei Shang
• Keywords: Background Suppression, Fuzzy Least Squares Support Vector Machines, Impurity Detection, Spatial-Temporal Correlation

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