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Segmentation and Recognition Algorithm for Chinese Handwritten Address Character String |
Fu Qiang Ding Xiao-qing Jiang Yan |
State Key Laboratory of Intelligent Technology and Systems, Department of Electronic Engineering, Tsinghua University, Beijing 100084, China |
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Abstract An effective segmentation and recognition method of Chinese handwritten address strings is proposed. Firstly, over-segmentation is applied to character string images by extracting stroke and merging them to obtain “radical” sequences. Next, the optimal segmentation and recognition result is achieved by synthesizing geometric analysis, isolated character classifier and semantic information together. The geometric information is estimated on current character string to adapt to various writing styles of character strings. The isolated character classifier adopts MQDF classifier with ten candidate results and their confidence. The semantic information is described by a character-based bi-gram model, parameters of which are estimated from a database containing 180,000 addresses items. The algorithm is tested on 3,000 actual handwritten address samples and the single-character recognition rate is 88.28%.
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Received: 15 June 2007
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Corresponding Authors:
Fu Qiang
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