Character recognition by algebraic invariant matrix

Yong-Qing Cheng; Ren Jiang; Yong-Ge Wu; Ke Liu; Jingyu Yang

doi:10.1117/12.138449

1 October 1992 Character recognition by algebraic invariant matrix

Yong-Qing Cheng, Ren Jiang, Yong-Ge Wu, Ke Liu, Jingyu Yang

Proceedings Volume 1705, Visual Information Processing; (1992) https://doi.org/10.1117/12.138449
Event: Aerospace Sensing, 1992, Orlando, FL, United States

Abstract

This paper introduces a robust method which can be used to recognize English characters. In our method, we first present an Invariant Matrix (IM) corresponding to a unique character image under the polar system. This kind of matrix has many properties and it is insensitive to image translation, scaling rotation and noise. On the basis of invariant matrix, a set of similar discriminant functions (SDF) of English characters are established. Then, a feature extraction and recognition method based on the SDF functions is proposed. Feature vectors extracted by our method are reliable and have the maximum similarity for the same class of English character samples. Finally, according to our recognition model, we design a hierarchical classifier to recognize English characters. Experimental results show that the SDF function based on IM is an efficient criterion for feature extraction of English characters and our recognition model can obtain the recognition accuracies of 100 percent for all English characters.

Citation Download Citation

Yong-Qing Cheng, Ren Jiang, Yong-Ge Wu, Ke Liu, and Jingyu Yang "Character recognition by algebraic invariant matrix", Proc. SPIE 1705, Visual Information Processing, (1 October 1992); https://doi.org/10.1117/12.138449

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