TY - GEN
T1 - Building a Compact MQDF Classifier by Sparse Coding and Vector Quantization Technique
AU - Wei, Xiaohua
AU - Lu, Shujing
AU - Lu, Yue
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - The modified quadratic discriminant function (MQDF) is a very popular handwritten Chinese character classifier thanks to its high performance with low computational complexity. However, it suffers from high memory requirement for the storage of its parameters. This paper proposes a compact MQDF classifier developed by integrating sparse coding and vector quantization (VQ) technique. To be specific, we use sparse coding to represent the parameters of MQDF in sparsity first, and then employ the VQ technique to further compress the sparse coding. The proposed method is evaluated by comparing the performance with three models, i.e., the original MQDF classifier, the compact MQDF classifier using the VQ technique, and the compact MQDF classifier using sparse coding. The effectiveness of our proposed approach has been confirmed and demonstrated by comparative experiments on ICDAR2013 competition dataset.
AB - The modified quadratic discriminant function (MQDF) is a very popular handwritten Chinese character classifier thanks to its high performance with low computational complexity. However, it suffers from high memory requirement for the storage of its parameters. This paper proposes a compact MQDF classifier developed by integrating sparse coding and vector quantization (VQ) technique. To be specific, we use sparse coding to represent the parameters of MQDF in sparsity first, and then employ the VQ technique to further compress the sparse coding. The proposed method is evaluated by comparing the performance with three models, i.e., the original MQDF classifier, the compact MQDF classifier using the VQ technique, and the compact MQDF classifier using sparse coding. The effectiveness of our proposed approach has been confirmed and demonstrated by comparative experiments on ICDAR2013 competition dataset.
KW - Compact MQDF classifier
KW - Sparse coding
KW - Vector quantization technique
UR - https://www.scopus.com/pages/publications/85045197140
U2 - 10.1109/ICDAR.2017.81
DO - 10.1109/ICDAR.2017.81
M3 - 会议稿件
AN - SCOPUS:85045197140
T3 - Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
SP - 454
EP - 459
BT - Proceedings - 14th IAPR International Conference on Document Analysis and Recognition, ICDAR 2017
PB - IEEE Computer Society
T2 - 14th IAPR International Conference on Document Analysis and Recognition, ICDAR 2017
Y2 - 9 November 2017 through 15 November 2017
ER -