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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Shengchang Chen Shujing Lu Ying Wen Yue Lu |
| Copyright Year | 2015 |
| Description | Author affiliation: Dept. of Comput. Sci. & Technol., East China Normal Univ., Shanghai, China (Shengchang Chen; Ying Wen; Yue Lu) || China Post Group, Shanghai Res. Inst., Shanghai, China (Shujing Lu) |
| Abstract | Different recognizers may result in different mistakes when they are used to recognize a Chinese address. In this paper, we present a method of combining multiple Chinese address recognition outputs to improve Chinese address recognition accuracy. The method first employs multiple sequence alignment to generate a lattice of candidate hypotheses from multiple different recognizer outputs and then applies statistical language model to choose the maximum likelihood candidate sequence. Taking the maximum as the final decision, the performance of our method is superior, compared to the single recognizers and Miyao's method. The experiments on the address images of real envelopes demonstrate that the proposed method increases the character recognition accuracy rate from 95.80% to 98.38%, with 61.30% error reduction. Furthermore, the corrected sorting rate of an automatic mail sorting system increases from 84.11% to 93.72%. |
| Starting Page | 151 |
| Ending Page | 155 |
| File Size | 728367 |
| Page Count | 5 |
| File Format | |
| e-ISBN | 9781479918058 |
| DOI | 10.1109/ICDAR.2015.7333742 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-08-23 |
| Publisher Place | Tunisia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image segmentation Training Optical character recognition software minimum edit distance multiple sequence alignment multiple Chinese address recognition outputs statistical language model |
| Content Type | Text |
| Resource Type | Article |
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