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A new hybrid approach to handwritten address verification

机译:手写地址验证的新混合方法

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The use of optical character recognition (OCR) has achieved considerable success in the sorting of machine-printed mail. The automatic reading of unconstrained handwritten addresses however, is less successful. This is due to the high error rate caused by the wide variability of handwriting styles and writing implements. This paper describes a strategy for automatic handwritten address reading which integrates a postcode recognition system with a hybrid verification stage. The hybrid verification system seeks to reduce the error rate by correlating the postcode against features extracted and words recognised from the remainder of the handwritten address. Novel use of syntactic features extracted from words has resulted in a significant reduction in the error rate while keeping the recognition rate high. Experimental results on a testset of 1,071 typical Singapore addresses showed a significant improvements from 24.0% error rate, 71.2% correct recognition rate, and 4.8% rejection rate using "raw" OCR postcode recognition to 0.4% error rate, 65.1% correct recognition rate, and 34.5% rejection rate using the hybrid verification approach. The performance of the approach compares favourably with the currently installed commercial system at Singapore Post, which achieved 0.7% error rate, 47.8% correct recognition rate, and 51.5% rejection rate for 6-digit postcode using the same test data.
机译:光学字符识别(OCR)的使用在对机器打印邮件的分类中取得了相当大的成功。但是,自动读取不受约束的手写地址不太成功。这是由于手写样式和书写工具的广泛差异导致的高错误率。本文介绍了一种自动手写地址读取策略,该策略将邮政编码识别系统与混合验证阶段集成在一起。混合验证系统试图通过将邮政编码与提取的特征和从手写地址的其余部分识别出的单词相关联来降低错误率。从单词提取的句法特征的新颖使用已导致错误率显着降低,同时保持了较高的识别率。在1071个典型新加坡地址的测试集上进行的实验结果表明,使用“原始” OCR邮政编码识别的错误率从24.0%,正确识别率和41.2%显着提高到0.4%,正确识别率65.1%,显着提高,使用混合验证方法的拒绝率为34.5%。该方法的性能优于新加坡邮政当前安装的商业系统,该系统在使用相同测试数据的情况下对6位数邮政编码实现了0.7%的错误率,47.8%的正确识别率和51.5%的拒绝率。

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