Scene character recognition using PCANet
Chongmu Chen, Da‐Han Wang, Hanzi Wang · 2015
Scene character recognition is capturing increasing interests due to the renewed interests in scene text recognition. For scene character recognition, feature representation is an important issue, which has been pursued in recent years. In this paper, we propose to use PCANet (principal component analysis network) to learn character features for scene character recognition. PCANet is proposed in [1], and it is a kind of deep learning framework by cascading PCA as in convolution neural network. In this paper, we apply PCANet to scene character recognition by customizing the architectures of PCANet to characters. The proposed method achieves promising performance on the Chars74K-15 dataset (achieving an accuracy of 64%) and the ICDAR03-CH dataset (achieving an accuracy of 75%), demonstrating the effectiveness of PCANet in scene character recognition.