Unsupervised image segmentation with the self-organizing map and statistical methods

Jukka Iivarinen; Ari J. E. Visa

doi:10.1117/12.325796

6 October 1998 Unsupervised image segmentation with the self-organizing map and statistical methods

Jukka Iivarinen, Ari J. E. Visa

Proceedings Volume 3522, Intelligent Robots and Computer Vision XVII: Algorithms, Techniques, and Active Vision; (1998) https://doi.org/10.1117/12.325796
Event: Photonics East (ISAM, VVDC, IEMB), 1998, Boston, MA, United States

Abstract

In this paper a special type of image segmentation, a two- class segmentation, is considered. Defect detection in quality control applications is a typical two-class problem. The main idea in this paper is to train the two-class classifier with fault-free samples that is an unexpected approach. The reason is that defects are rare and expensive. The proposed defect detection is based on the following idea: an unknown sample is classified as a defect if it differs enough from the estimated prototypes of fault-free samples. The self-organizing map is used to estimate these prototypes. Surface images are used to demonstrate the proposed image segmentation procedure.

Citation Download Citation

Jukka Iivarinen and Ari J. E. Visa "Unsupervised image segmentation with the self-organizing map and statistical methods", Proc. SPIE 3522, Intelligent Robots and Computer Vision XVII: Algorithms, Techniques, and Active Vision, (6 October 1998); https://doi.org/10.1117/12.325796

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