TY - JOUR
T1 - Wavelet orthonormal decompositions for extracting features in pattern recognition
AU - Tang, Yuan Y.
AU - LIU, Jiming
AU - Ma, Hong
AU - Li, Bing F.
N1 - Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 1999/9
Y1 - 1999/9
N2 - In this paper, a novel approach based on the wavelet orthonormal decomposition is presented to extract features in pattern recognition. The proposed approach first reduces the dimensionality of a two-dimensional pattern, and thereafter performs wavelet transform on the derived one-dimensional pattern to generate a set of wavelet transform subpatterns, namely, several uncorrelated functions. Based on these functions, new features are readily computed to represent the original two-dimensional pattern. As an application, experiments were conducted using a set of printed characters with varying orientations and fonts. The results obtained from these experiments have consistently shown that the proposed feature vectors can yield an excellent classification rate in pattern recognition.
AB - In this paper, a novel approach based on the wavelet orthonormal decomposition is presented to extract features in pattern recognition. The proposed approach first reduces the dimensionality of a two-dimensional pattern, and thereafter performs wavelet transform on the derived one-dimensional pattern to generate a set of wavelet transform subpatterns, namely, several uncorrelated functions. Based on these functions, new features are readily computed to represent the original two-dimensional pattern. As an application, experiments were conducted using a set of printed characters with varying orientations and fonts. The results obtained from these experiments have consistently shown that the proposed feature vectors can yield an excellent classification rate in pattern recognition.
UR - http://www.scopus.com/inward/record.url?scp=0033344915&partnerID=8YFLogxK
U2 - 10.1142/S0218001499000458
DO - 10.1142/S0218001499000458
M3 - Journal article
AN - SCOPUS:0033344915
SN - 0218-0014
VL - 13
SP - 803
EP - 831
JO - International Journal of Pattern Recognition and Artificial Intelligence
JF - International Journal of Pattern Recognition and Artificial Intelligence
IS - 6
ER -