Real-time flaw detection on a complex object: comparison of results using classification with a support vector machine, boosting, and hyperrectangle-based method

Johel Miteran; S. Bouillant; Michel Paindavoine; Fabrice Meriaudeau; Julien Dubois

doi:10.1117/1.2179436

1 January 2006 Real-time flaw detection on a complex object: comparison of results using classification with a support vector machine, boosting, and hyperrectangle-based method

Johel Miteran, S. Bouillant, Michel Paindavoine, Fabrice Meriaudeau, Julien Dubois

Author Affiliations +

Journal of Electronic Imaging, Vol. 15, Issue 1, 013018 (January 2006). https://doi.org/10.1117/1.2179436

Abstract

We present a classification work performed on industrial parts using artificial vision, a support vector machine (SVM), boosting, and a combination of classifiers. The object to be controlled is a coated heater used in television sets. Our project consists of detecting anomalies under manufacturer production, as well as in classifying the anomalies among 20 listed categories. Manufacturer specifications require a minimum of ten inspections per second without a decrease in the quality of the produced parts. This problem is addressed by using a classification system relying on real-time machine vision. To fulfill both real-time and quality constraints, three classification algorithms and a tree-based classification method are compared. The first one, hyperrectangle based, proves to be well adapted for real-time constraints. The second one is based on the Adaboost algorithm, and the third one, based on SVM, has a better power of generalization. Finally, a decision tree allowing improving classification performances is presented.

©(2006) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Johel Miteran, S. Bouillant, Michel Paindavoine, Fabrice Meriaudeau, and Julien Dubois "Real-time flaw detection on a complex object: comparison of results using classification with a support vector machine, boosting, and hyperrectangle-based method," Journal of Electronic Imaging 15(1), 013018 (1 January 2006). https://doi.org/10.1117/1.2179436

Published: 1 January 2006

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