Multiresolution moment-Fourier-wavelet descriptor for 2D pattern recognition

Tien D. Bui; Guangyi Chen

doi:10.1117/12.271746

Abstract

We propose an invariant descriptor for recognizing complex patterns and objects composed of closed regions such as printed Chinese characters. The method transforms a 2D image into 1D line moments, performs wavelet transform on the moments, and then applies Fourier transform on each level of the wavelet coefficients and the average. The essential advantage of the descriptor is that a multiresolution querying strategy can be employed in the recognition process and that it is invariant to shift, rotation, and scaling of the original image. Experimental results show that the descriptor proposed in this paper is a reliable tool for recognizing Chinese characters.

Citation Download Citation

Tien D. Bui, Tien D. Bui, Guangyi Chen, Guangyi Chen, } "Multiresolution moment-Fourier-wavelet descriptor for 2D pattern recognition", Proc. SPIE 3078, Wavelet Applications IV, (3 April 1997); doi: 10.1117/12.271746; https://doi.org/10.1117/12.271746

ACCESS THE FULL ARTICLE

PERSONAL SIGN IN
Full access may be available with your subscription

Email or Username Forgot your username?

Password Forgot your password?

Show

Remember Email/Username on this computer

Remember Password

No SPIE account? Create an account
or Institutional Sign In via Shibboleth

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

Members: $14.40

Non-members: $18.00 ADD TO CART

Show All Keywords

Keywords/Phrases

Search In:

Publication Years