Multisensor fusion for geometric-part inspection

George K. Knopf; Jonathan Kofman

doi:10.1117/12.371188

24 November 1999 Multisensor fusion for geometric-part inspection

George K. Knopf, Jonathan Kofman

Proceedings Volume 3832, Sensors and Controls for Intelligent Machining and Manufacturing Mechatronics; (1999) https://doi.org/10.1117/12.371188
Event: Photonics East '99, 1999, Boston, MA, United States

Abstract

Multiple off-the-shelf cameras can be configured to simultaneously provide a large variety of part features that are impossible to capture with a single CCD camera or range scanner. One unsolved problem is using several cameras for passive shape recognition is that of multi-view registration. Registration is the process of associating the feature vectors extracted from the image captured by one camera view with that from another view. This paper describes an unsupervised clustering algorithm used to associate redundant and complementary features extracted from different views of a 3D object for part identification and inspection. The unsupervised learning algorithm ensures that 'similar' feature vectors will be assigned to cluster units that lie in close spatial proximity in a 3D feature map. The technique reduces the dimensionality of the input by exploiting hidden redundancies in the training data. During the inspection phase, novel features activate a number of cluster nits that have weights similar to the applied training data. During the inspection phase, novel features activate a number of cluster units that have weights similar to the applied training input. If the sum- of-square error between the input and weights of the cluster unit with the strongest response is greater than a predefined tolerance, then the part is rejected. A simulation study is presented to illustrate how the proposed multi-sensor fusion technique can be applied to identifying parts for inspection.

Citation Download Citation

George K. Knopf and Jonathan Kofman "Multisensor fusion for geometric-part inspection", Proc. SPIE 3832, Sensors and Controls for Intelligent Machining and Manufacturing Mechatronics, (24 November 1999); https://doi.org/10.1117/12.371188

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