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A post-processing approach to Chinese address recognition

A post-processing approach to Chinese address recognition

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2011 8th International Conference on Fuzzy systems and Knowledge Discovery, FSKD 2011, jointly with the 2011 7th International Conference on Natural Computation, ICNC'11

作者： Yao, Xinyu Lu, Yue Department of Computer Science and Technology East China Normal University Shanghai 200241 China ECNU-SRI Joint Lab for Pattern Analysis and Intelligent System Shanghai Research Institute of China Post Group Shanghai 200062 China

ISBN: (纸本)9781612841816

In recent years, it has become a focus to make use of the address recognition technology to improve the performance of mail sorting machines. The research in the postal address recognition, which extends the context relation from words to sentences with the use of the address information in post-processing, can effectively improve the recognition performance. In this paper, we propose a divide-and-rule method. The address is divided into high level address and low level address. For high level address, the similarity method with HLA database is presented. For low level address, the Syllable-based language model which applies to Pinyin is discussed. Then a new similarity method in multi-mode is introduced. After post-processing, for high level address, the hit rate rises from 87.63% to 95.12% while the accuracy rate declines by 2.67%, and for low level address, the hit rate increases from 58.16% to 91.81% while the accuracy rate decreases by 9.40%. © 2011 IEEE.

关键词： OCR fuzzy match post-processing similarity hit rate similarity method accuracy rate LOW LEVEL POST-PROCESSING modelling languages

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Text extraction from mail images with complex background 14th

Text extraction from mail images with complex background

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14th International Forum of Digital TV and Wireless Multimedia Communication, IFTC 2017

作者： Wang, Qingqing Tu, Xiao Lu, Shujing Lu, Yue Department of Computer Science and Technology East China Normal University Shanghai200062 China ECNU-SRI Joint Lab for Pattern Analysis and Intelligent Shanghai Research Institute of China Post Group Shanghai200062 China

ISBN: (纸本)9789811081071

A novel method is proposed for text extraction from mail images with complex background. Firstly, wavelet transform and Laplacian operator are applied to generate the features of regions which are obtained by dividing input image with sliding window. Then, support vector machine (SVM) is utilized to classify these regions into texts and non-texts according to the features. Bootstrap strategy is used to build the training database. Finally, connected components analysis (CCA) is employed to merge text regions into text candidates which can be processed by following steps to get the delivery address. Experimental results involving 534 mail images show the effectiveness and robustness of the proposed method, and comparison results with other methods demonstrate the advantages of the selected features. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Wavelet transforms

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Application of PR techniques to mail sorting in China

Application of PR techniques to mail sorting in China

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2014 7th International C Conference on Computer Science and Software Engineering, C3S2E 2014

作者： Liu, Li Lu, Shujing Lu, Yue Suen, Ching Y. Department of Computer Science and Technology East China Normal University Shanghai 200241 China ECNU-SRI Joint Lab. for Pattern Analysis and Intelligent System Shanghai Research Institute of China Post Group Shanghai 200062 China Centre for Pattern Recognition and Machine Intelligence Concordia University Montreal QC H3G 1M8 Canada

ISBN: (纸本)9781450327121

Mail sorting machines play an important role in postal automation. In this paper, we give a brief overview of mail sorting machines in China Post from a pattern recognition point of view. OCR techniques such as postcode recognition and address recognition are essential for mail sorting machines, which are considered as class imbalance problems in our study. In addition to OCR that mainly focuses on the characters in the image, some image-level features are exploited for near-duplicate envelope image matching, which is helpful in tracking pieces of mail in the network environment. © 2014 ACM.

关键词： Image matching

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Cost-Sensitive Transformation for Chinese Address Recognition

Cost-Sensitive Transformation for Chinese Address Recognitio...

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International Conference on pattern Recognition

作者： Shujing Lu Xiaohua Wei Yue Lu ECNU-SRI Joint Lab for Pattern Analysis and Intelligent System Shanghai Research Institute of China Post Shanghai China Department of Computer Science and Technolozy East China Normal University Shanghai China

ISBN: (纸本)9781479952106

This paper proposes a cost-sensitive transformation for improving handwritten address recognition performance by converting a general-purpose handwritten Chinese character recognition engine to a special-purpose one. The class probabilities produced by character recognition engine for predicting a sample to candidate classes are transformed to the expected costs based on Naive Bayes optimal theoretical predictions firstly. And then candidate probabilities are reestimated based on the expected costs. Two general-purpose offline handwritten Chinese character recognition engines, PAIS and HAW, are tested in our experiments by applying them in handwritten Chinese address recognition system. 1822 live handwritten Chinese address images are tested with multiple cost matrices. Experimental results show that cost-sensitive transformation improves the recognition performance of general purpose recognition engines on handwritten Chinese address recognition.

关键词： Character recognition Engines Image recognition Image segmentation Handwriting recognition Lattices

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Using multiple sequence alignment and statistical language model to integrate multiple Chinese address recognition outputs

Using multiple sequence alignment and statistical language m...

引用

International Conference on Document analysis and Recognition

作者： Shengchang Chen Shujing Lu Ying Wen Yue Lu Department of Computer Science and Technology East China Normal University Shanghai China ECNU-SRI Joint Lab for Pattern Analysis and Intelligent System Shanghai Research Institute of China Post Group Shanghai China

ISBN: (纸本)9781479918065

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%.

关键词： Image segmentation Training Optical character recognition software

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Cost-sensitive MQDF classifier for handwritten Chinese address recognition

Cost-sensitive MQDF classifier for handwritten Chinese addre...

引用

International Conference on Document analysis and Recognition

作者： Shujing Lu Xiaohua Wei Yue Lu ECNU-SRI Joint Lab for Pattern Analysis and Intelligent System Shanghai Research Institute of China Post Shanghai China Processing Department of Computer Science and Technology East China Normal University Shanghai China

ISBN: (纸本)9781479918065

To overcome the class imbalance problem in Chinese address recognition, we propose a cost-sensitive learning method for MQDF classifier. In the learning process, a cost vector is introduced to the discriminative learning process of MQDF, and minimization of misclassification cost is used as the convergence criteria. A cost-sensitive MQDF classifier (CMQDF) is then obtained, and it is integrated into a handwritten Chinese address recognition (HCAR) system to validate its effectiveness. The experimental results show that CMQDF is an effective cost-sensitive classifier for the class imbalance problem in HCAR system. Moreover, it enhances the reliability of the HCAR system.

关键词： Optical sensors Internet

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EXPRESS WAYBILL EXTRACTION ON PARCEL IMAGES BY LOGO MATCHING

EXPRESS WAYBILL EXTRACTION ON PARCEL IMAGES BY LOGO MATCHING

引用

IEEE International Conference on Image Processing

作者： Shujing Lu Jie Zhao Yue Lu ECNU-SRI Joint Lab for Pattern Analysis and Intelligent System Shanghai Research Institute of China Post Group Shanghai Key Laboratory of Multidimensional Information Processing Department of Computer Science and Technology East China Normal University

ISBN: (纸本)9781467399623

We propose an efficient method for automatically extracting express waybills from parcel images, which is challenging due to varied resolution of parcel images, arbitrary direction of waybills and different information filled by senders. To address these challenges, logo matching is employed to extract the waybills. We begin by extracting scale-invariant feature-transformation (SIFT) keypoints from both the reference logo image and a parcel image, and matching them subject to a consistent projective transformation (homography) by using random sample consensus (RANSAC). Once the homography matrix is computed, we extract the waybill of parcel image by mapping all pixels from a standard waybill image to the parcel image. Experimental results on test datasets demonstrate the effectiveness of the proposed method.

关键词： Logo matching Express waybill extraction SIFT images Sifting Fields LOGO Imagery (Psychotherapy) Image homography

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Binarization of degraded document image using Gaussian Markov random field model

Binarization of degraded document image using Gaussian Marko...

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International Conference on Audio, Language and Image Processing, ICALIP

作者： Shujing Lu Yue Lu ECNU-SRI Joint Lab for Pattern Analysis and Intelligence System Shanghai Research Institute of China Post Group Shanghai China Department of Computer Science and Technology East China Normal University Shanghai China

ISBN: (纸本)9781479939046

This paper presents a binarization approach to degraded document images, which is based on Gaussian Markov Random Field (GMRF) model. The energy function with the single-site and pair-site clique potential functions is formulated for the GMRF. The parameters of the potential functions are estimated by expectation-maximization (EM) algorithm, without necessity of training process. Experiments on different types of degraded document images with various noise, contrast variation or uneven illumination, have demonstrated the validity of the proposed method.

关键词： Markov random fields Computational modeling Mathematical model Probability density function Convergence pattern recognition Analytical models

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Image feature based method for mail retrieval

Image feature based method for mail retrieval

引用

Chinese Conference on pattern Recognition

作者： Du, Yuxiao Lu, Yue Department of Computer Science and Technology East China Normal University Shanghai 200241 China ECNU-SRI Joint Lab. of Pattern Analysis and Intelligence System Shanghai Research Institute China Post Group Shanghai 200062 China

ISBN: (纸本)9781424472109

A mail retrieval method based on image feature is an innovative approach by which the postal department can realize the query of mail information. The paper chooses envelope images with handwritten address characters as retrieval object. Through a series of researches on a large number of image features, we select partition-block image feature, projection histogram feature and SIFT feature to construct feature vector. In order to accelerate processing speed, we optimize the retrieval procedure by matching feature component in multiple levels. The experimental results and comparative analysis have demonstrated that the precision of the proposed retrieval system reaches at least 99%, which proves the practicability and robustness of the method. ©2010 IEEE.

关键词： Graphic methods

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