Due to the rapid development of mobile devices equipped with cameras, instant translation of any text seen in any context is possible. Mobile devices can serve as a translation tool by recognizing the texts presented in the captured scenes. Images captured by cameras will embed more external or unwanted effects which need not to be considered in traditional optical character recognition (OCR). In this paper, we segment a text image captured by mobile devices into individual single characters to facilitate OCR kernel processing. Before proceeding with character segmentation, text detection and text line construction need to be performed in advance. A novel character segmentation method which integrates touched character filters is employed on text images captured by cameras. In addition, periphery features are extracted from the segmented images of touched characters and fed as inputs to support vector machines to calculate the confident values. In our experiment, the accuracy rate of the proposed character segmentation system is 94.90%, which demonstrates the effectiveness of the proposed method.

A new approach to stroke-order and stroke-number free on-line handwritten Chinese character recognition is presented in this paper. In this new scheme, the decision rule of the segment attribute is used to characterize the segment sequence appearing in each Chinese character for reco@izing connected-stroke and even cursive handwritten Chinese characters. A knowledge-based radical extraction method is proposed to perform the feature extraction before radical recognition stage. The top-level and bottom-level radical classification are adopted in the coarse classification stage to reduce the number of candidate characters. In order to develop a stroke order free system, the neighboring segment matching method is proposed. Experimental results show that the proposed scheme is an efficient solution for stroke-order and stroke-number free on-line Chinese character recognition. The recognition rate is 93.4% and the recognition speed is 0.6 second per character.

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