Shape completion for automatic inspection

Adrian Preston; Peter Forte

doi:10.1117/12.248567

21 August 1996 Shape completion for automatic inspection

Adrian Preston, Peter Forte

Proceedings Volume 2786, Vision Systems: Applications; (1996) https://doi.org/10.1117/12.248567
Event: Lasers, Optics, and Vision for Productivity in Manufacturing I, 1996, Besancon, France

Abstract

In this paper we outline an approach to a fast low-cost system for the inspection and evaluation of surface-mount assemblies and solder joints, giving particular focus to the need for robustness in such a system. We describe the software modules involved in extracting features, and shape analysis for the purpose of inspection. A common problem during the early stages of image processing is the loss of information about the edges of shape because of noise, weak contrast, or occlusion, which often increases the amount of incorrect interpretations of a given image when presented to higher levels of processing. An algorithm is described which significantly reduces the effect of such problems before information is passed to later stages of the vision process. The algorithm, which uses information about contour to correct dropouts is generic, employing no application specific information and is therefore applicable to vision systems in general.

Citation Download Citation

Adrian Preston and Peter Forte "Shape completion for automatic inspection", Proc. SPIE 2786, Vision Systems: Applications, (21 August 1996); https://doi.org/10.1117/12.248567

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available