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A Mobile Chinese Character Image Recognition Platform

机译:移动汉字图像识别平台

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People may have difficulty in reading Chinese books because there always exist some unfamiliar Chinese characters, so it would be valuable if an application can help users including foreigners to learn them. This paper presents a platform based on mobile devices for helping people to recognize the unfamiliar characters at any time or any place. Firstly, we collect various dataset of Chinese characters to build a complete character set, then create the image library according to that set by segmenting. Secondly, the so-called GIST and SIFT features are extracted from the image library to establish feature library. To improve the recognition performance, we filter the SIFT feature points of similar images obtained by GIST feature matching. Finally, compress the storage of GIST and SIFT descriptors to accommodate mobile platform with Similarity Sensitive Coding (SSC) algorithm. At the stage of recognition, the high-dimensional indexing algorithm is applied in finding the top k Chinese characters similar to the image of unfamiliar character by GIST feature, which has the strong versatility and the extension malleability. Then these characters are reordered by SIFT feature matching. The final recognition result is based on the locations of each character in GIST and SIFT matching result respectively. We apply that algorithm in Android platform. It shows great performance in recognition and gives smooth experience to users.
机译:人们可能很难阅读中文书籍,因为总是存在一些陌生的汉字,因此,如果应用程序可以帮助包括外国人在内的用户学习它们,那将很有价值。本文提出了一个基于移动设备的平台,可以帮助人们在任何时间,任何地点识别陌生的字符。首先,我们收集各种汉字数据集以建立完整的字符集,然后根据该图像集进行分割以创建图像库。其次,从图像库中提取所谓的GIST和SIFT特征,以建立特征库。为了提高识别性能,我们对通过GIST特征匹配获得的相似图像的SIFT特征点进行了过滤。最后,使用相似敏感编码(SSC)算法压缩GIST和SIFT描述符的存储,以适应移动平台。在识别阶段,采用高维索引算法通过GIST特征查找与陌生字符图像相似的前k个汉字,具有较强的通用性和可扩展性。然后,通过SIFT功能匹配对这些字符进行重新排序。最终的识别结果分别基于每个字符在GIST和SIFT匹配结果中的位置。我们将该算法应用于Android平台。它在识别方面显示出出色的性能,并为用户提供流畅的体验。

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