Target recognition under projective transformation

Wei An; Zhongkang Sun; Hui Xu; Hong Li; Xiong Hui

doi:10.1117/12.270354

27 March 1997 Target recognition under projective transformation

Wei An, Zhongkang Sun, Hui Xu, Hong Li, Xiong Hui

Proceedings Volume 3073, Optical Pattern Recognition VIII; (1997) https://doi.org/10.1117/12.270354
Event: AeroSense '97, 1997, Orlando, FL, United States

Abstract

Projective transformation (PT) is the most general transformation in nature. However, as it is nonlinear, people haven't made great progress in the research of projective invariant. On the other hand, many researchers are confused with PT and affine transformation (AT), they used projective deformed patterns testify affine invariants without any additional explanation. This paper has thoroughly studied PT and AT. When the fixed point or fixed axis of PT is on some special positions, PT degenerates into linear form - AT. In other cases, PT can be approximated as AT under certain condition. In this paper we derived a formula of relation between them and analyzed the errors arising from this approximation. It leads a new way to recognize projective deformed patterns. Three new independent affine moment invariants composed of second- or third-order central moments are adopted for 2D and 3D target recognition. The simulation experiment reached a satisfying result.

Citation Download Citation

Wei An, Zhongkang Sun, Hui Xu, Hong Li, and Xiong Hui "Target recognition under projective transformation", Proc. SPIE 3073, Optical Pattern Recognition VIII, (27 March 1997); https://doi.org/10.1117/12.270354

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