An improved handwritten Chinese character recognition system using support vector machine
Pattern Recognition Letters - Special issue: Artificial neural networks in pattern recognition
A note on Platt's probabilistic outputs for support vector machines
Machine Learning
Hanzi Lamp: an intelligent guide interface for Chinese character learning
Proceedings of the adjunct publication of the 26th annual ACM symposium on User interface software and technology
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With the recent rise of China, Chinese is becoming a dominant language in the world. People are pursuing an efficient and effective means to learn the Chinese language. Most of the traditional learning platforms such as textbooks, laptop applications and language learning centers are not portable and interactive simultaneously. In this paper, we attempt to develop a new language-learning platform that not only creates a better user experience but also promotes better efficiency in language training. We present a mobile application named HuayuNavi that integrates a touch-based user interface with intelligent character recognition techniques to achieve real-time image content understanding. Specifically, the feature vector is formed by accumulating localized gradients of different orientations in the image. Recognition is achieved by employing support vector machine (SVM) with probability estimation to obtain candidate characters, which is then refined using domain-specific vocabulary models. The overall operation can be completed in 3 seconds. Initial tests on the specific subject of Taiwanese snacks indicate that the recognition rate can reach 83% using handwritten samples as well as signboards containing characters of diverse fonts.