Statistical-learning-based object recognition algorithm for solder joint inspection

Kyoungchul Koh; H.J. Choi; Jae-Seon Kim; Hyungsuck Cho

doi:10.1117/12.444096

4 October 2001 Statistical-learning-based object recognition algorithm for solder joint inspection

Kyoungchul Koh, H.J. Choi, Jae-Seon Kim, Hyungsuck Cho

Proceedings Volume 4564, Optomechatronic Systems II; (2001) https://doi.org/10.1117/12.444096
Event: Intelligent Systems and Advanced Manufacturing, 2001, Boston, MA, United States

Abstract

As PCB components become more complex and smaller, the conventional inspection method using traditional ICT and function test show their limitations in application. On the contrary, the automatic optical inspection (AOI) gradually becomes the alternative in the PCB assembly line. In particular, the PCB inspection machines need more reliable and flexible object recognition algorithms for high inspection accuracy. The conventional AOI machines use the algorithmic approaches such as template matching. Fourier analysis, edge analysis, geometric feature recognition or optical character recognition, which mostly require much of teaching time and expertise of human operators. To solve this problem, in this paper, a statistical learning based part recognition method is proposed. The performance of the proposed approach is evaluated on numerous samples of real electronic part images. Experimental results demonstrate satisfactory performance and practical usefulness in PCB inspection processes.

Citation Download Citation

Kyoungchul Koh, H.J. Choi, Jae-Seon Kim, and Hyungsuck Cho "Statistical-learning-based object recognition algorithm for solder joint inspection", Proc. SPIE 4564, Optomechatronic Systems II, (4 October 2001); https://doi.org/10.1117/12.444096

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