A Novel Vision-Based Approach for Detection of Foreign Substances

Abstract:

Article Preview

The detection of foreign substances in injection so far is still achieved artificially, which result in low accuracy and low efficiency. This paper focuses on developing a novel vision-based approach for detection of foreign substances. Foreign substances are classified into two categories, subsiding-slowly object and subsiding-fast object. A relative movement caused by a motor helps to distinguished foreign substances from ampoule surface scratches. Moving objects in injection are divided from static ones by a background image derived from two frames. The Mean Shift Embedded Particle Filter (MSEPF) is proposed to detect moving-slowly object while Frame Distance is defined to detect moving-fast object. 200 ampoule samples filled with injection are tested. The integrated detection accuracy with this approach is 98.00%, with 97.56% accuracy for subsiding-slowly objects and 96.67% accuracy for subsiding-fast ones. The result shows that the system can detect foreign substances effectively.

Info:

Periodical:

Advanced Materials Research (Volumes 317-319)

Edited by:

Xin Chen

Pages:

847-853

DOI:

10.4028/www.scientific.net/AMR.317-319.847

Citation:

G. L. Lu et al., "A Novel Vision-Based Approach for Detection of Foreign Substances", Advanced Materials Research, Vols. 317-319, pp. 847-853, 2011

Online since:

August 2011

Export:

Price:

$35.00

In order to see related information, you need to Login.

In order to see related information, you need to Login.