Share Email Print

Proceedings Paper

Multiscale moment-based technique for object matching and recognition
Author(s): HweeLi Thio; Liya Chen; Eam-Khwang Teoh
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

A new method is proposed to extract features from an object for matching and recognition. The features proposed are a combination of local and global characteristics -- local characteristics from the 1-D signature function that is defined to each pixel on the object boundary, global characteristics from the moments that are generated from the signature function. The boundary of the object is first extracted, then the signature function is generated by computing the angle between two lines from every point on the boundary as a function of position along the boundary. This signature function is position, scale and rotation invariant (PSRI). The shape of the signature function is then described quantitatively by using moments. The moments of the signature function are the global characters of a local feature set. Using moments as the eventual features instead of the signature function reduces the time and complexity of an object matching application. Multiscale moments are implemented to produce several sets of moments that will generate more accurate matching. Basically multiscale technique is a coarse to fine procedure and makes the proposed method more robust to noise. This method is proposed to match and recognize objects under simple transformation, such as translation, scale changes, rotation and skewing. A simple logo indexing system is implemented to illustrate the performance of the proposed method.

Paper Details

Date Published: 21 March 2000
PDF: 11 pages
Proc. SPIE 3966, Machine Vision Applications in Industrial Inspection VIII, (21 March 2000); doi: 10.1117/12.380064
Show Author Affiliations
HweeLi Thio, Nanyang Technological Univ. (Singapore)
Liya Chen, Nanyang Technological Univ. (Singapore)
Eam-Khwang Teoh, Nanyang Technological Univ. (Singapore)

Published in SPIE Proceedings Vol. 3966:
Machine Vision Applications in Industrial Inspection VIII
Kenneth W. Tobin Jr.; John C. Stover, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?