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Proceedings Paper

Application of adaptive texture filters to the automated visual inspection of antibiotic susceptibility tests
Author(s): David Zhengwen Zhang; Simon Snowden; Jia-Chang Wang; David Kind
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Paper Abstract

Computer vision systems have been used in recent years to perform automated antibiotic susceptibility test based on the disk-diffusion method. However, certain organisms do not reflect light very well. As such, the reliability of such automated inspection systems is sometimes not as high as expected. This paper proposes to use texture analysis to improve the quality of test images and thereby simplify the inspection tasks. Adaptive texture filters are used to maximize the difference between regions of interest in a test image and the background, enabling a thresholding operation to be carried out easily. The principles of adaptive filtering for texture analysis are discussed. A training algorithm is presented to generate optimized filters for generic texture inspection problems. An experimental study is carried out to investigate the performance of this technique in highlighting poorly reflecting organisms in antibiotic susceptibility testes.

Paper Details

Date Published: 17 December 1998
PDF: 7 pages
Proc. SPIE 3518, Sensors and Controls for Intelligent Machining, Agile Manufacturing, and Mechatronics, (17 December 1998); doi: 10.1117/12.332805
Show Author Affiliations
David Zhengwen Zhang, Univ. of Liverpool (United Kingdom)
Simon Snowden, Mast Group Ltd. (United Kingdom)
Jia-Chang Wang, Univ. of Liverpool (United Kingdom)
David Kind, Univ. of Liverpool (United Kingdom)

Published in SPIE Proceedings Vol. 3518:
Sensors and Controls for Intelligent Machining, Agile Manufacturing, and Mechatronics
Patrick F. Muir; Patrick F. Muir; Peter E. Orban, Editor(s)

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