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In the area of multi-label image categorization, there are two important issues: label classification and label ranking. The former refers to whether a label is relevant or not, and the latter refers to what extent a label is relevant to an image. However, few existing papers have considered them in a holistic way. In this paper we will suggest a concrete(More)
Conventional Binarization methods try to obtain optimal results based on the single image only. They make distinct diversity of binarization quality sometimes even for images of the same documents. Using a binarization evaluation and feedback mechanism, this paper proposed a learning-based binarization method which can improve the binarization of same-type(More)
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(More)