Machine vision system for positioning and part verification of gas oil filters based on eigenimages

Franci Lahajnar; Stanislav Kovacic

doi:10.1117/12.380076

21 March 2000 Machine vision system for positioning and part verification of gas oil filters based on eigenimages

Franci Lahajnar, Stanislav Kovacic

Proceedings Volume 3966, Machine Vision Applications in Industrial Inspection VIII; (2000) https://doi.org/10.1117/12.380076
Event: Electronic Imaging, 2000, San Jose, CA, United States

Abstract

A PC based machine vision system is described, designed for precise positioning and reliable recognition of gas oil filters. The system has been integrated into the production line, which is capable of assembling several types of filters, each one having its own visual appearance. Our primary goal was to design a flexible system, which could be easily adapted for assembling different filter types. To achieve this an appearance based method, employing the Karhunen-Loeve expansion, was used. Based on this method, the most significant visual information is automatically extracted from a set of rotated filter images, i.e. templates, and described by a small number of eigenimages. The eigenimages constitute the eigenspace. These templates and the captured image of the filter in an unknown position are projected to the eigenspace. The distances between the projected templates and the projected filter image are computed. Based on these distances, the filter position and its type are determined and the filter rotated. The system operates in a closed loop, therefore the new position can be evaluated and corrected, as required. The results obtained so far show that the system works reliably, and meets the required accuracy and speed.

Citation Download Citation

Franci Lahajnar and Stanislav Kovacic "Machine vision system for positioning and part verification of gas oil filters based on eigenimages", Proc. SPIE 3966, Machine Vision Applications in Industrial Inspection VIII, (21 March 2000); https://doi.org/10.1117/12.380076

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