Real-time classification of wooden boards

Wolfgang Poelzleitner; Gert Schwingskakl

doi:10.1117/12.25308

1 February 1991 Real-time classification of wooden boards

Wolfgang Poelzleitner, Gert Schwingskakl

Proceedings Volume 1384, High-Speed Inspection Architectures, Barcoding, and Character Recognition; (1991) https://doi.org/10.1117/12.25308
Event: Advances in Intelligent Robotics Systems, 1990, Boston, MA, United States

Abstract

In this paper the design of a prototype system for real-time classification of wooden profiled boards is described. The presentation gives an overview of the algorithms and hardware developed to achieve classification in real-time at a data rate of 4Mpixel/sec. The system achieves its performance by a hierarchical processing strategy where the intensity information in the digital image is transformed into a symbolic description of small texture elements. Based on this symbolic representation a syntactic segmentation scheme is applied which produces a list of objects that are present on the board surface. The objects are described by feature vectors containing both numeric structural texture- and shape-related properties. A graph-like decision network is then used to recognize the various defects. The classification procedures were extensively tested for spruce boards on a large data set containing 500 boards taken from the production line at random. The overall rate of correct classification was 95 on this data set. The structure of these algorithms is reflected in the hardware design. We use a multiprocessor system where each processor is specialized to solve a specific task in the recognition hierarchy.

Citation Download Citation

Wolfgang Poelzleitner and Gert Schwingskakl "Real-time classification of wooden boards", Proc. SPIE 1384, High-Speed Inspection Architectures, Barcoding, and Character Recognition, (1 February 1991); https://doi.org/10.1117/12.25308

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