Separate Chinese Character and English Character by Cascade Classifier and Feature Selection

The separation of Chinese character and English character is helpful for OCR technique. In this paper, a multi-level cascade classifier combined with feature selection is constructed to identify Chinese character and English character based on individual character. Most of samples are identified by the first node classifier, the remained low classification confidence samples are fed to the next node classifiers to get the final result. For the motivation of utilizing feature complementarity, each node classifier is trained on low classification confidence samples of its previous node classifier with independent feature selection. Furthermore, a confidence bias is utilized to improve the classifier generalization. The experiment results validate the effectiveness of this classifier.

• Type: Journal
• Year: 2009
• Where: ICDAR
• Authors: Yuanping Zhu, Jun Sun 0004, Akihiro Minagawa, Yoshinobu Hotta, Satoshi Naoi
• Keywords: Classification Confidence Samples, Document Analysis, ICDAR 2009, Low Classification Confidence, Node Classifier