InforLorV4, Main, Merge, bibRecord, 005D23

A System for Indian Postal Automation

Identifieur interne : 005D23 ( Main/Merge ); précédent : 005D22; suivant : 005D24

A System for Indian Postal Automation

Auteurs : Kaushik Roy [Inde] ; Szilárd Vajda [France] ; Umapada Pal [Inde] ; Bidyut Baran Chaudhuri [Inde] ; Abdel Belaïd [France]

Source :

RBID : Hal:inria-00000103

English descriptors

mix :
- handwriting recognition, neural networks, postal automation, stochastic models.

Abstract

In this paper, we present a system towards Indian postal automation based on pin-code and city name information. In the proposed system, at first, non-text blocks (postal stamp, postal seal etc.) are detected and destination address block (DAB) is identified from the postal document. Next, lines and words of the DAB are segmented. Since India is a multi-lingual and multi-script country that was earlier colonized by UK, the address part may be written by combination of two scripts: Latin (English) and a local (state) script. Here we shall consider Bangla script (local state language) with English for recognition. It is very difficult to identify the script by which the pin-code portion is written. So we have used two-stage artificial neural network based general classifiers for the recognition of pin-code digits written in English/Bangla. To identify the script by which a word/city name is written, we propose a water reservoir based technique. Based on script identification result the city names on the corresponding script will be recognized. For recognition of city names we propose a NSHP-HMM (Non-Symmetric Half Plane-Hidden Markov Model) based technique. At present, the accuracy of the digit recognition module is 93.14% while that of city name recognition scheme is about 86.44%.

Url:

https://hal.inria.fr/inria-00000103

Links toward previous steps (curation, corpus...)

to stream Hal, to step Corpus: 000524
to stream Hal, to step Curation: 000524
to stream Hal, to step Checkpoint: 004717

Links to Exploration step

Hal:inria-00000103

Le document en format XML

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<date type="end">2011-12-31</date>
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<orgName type="acronym">INPL</orgName>
<date type="end">2011-12-31</date>
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<profileDesc><textClass><keywords scheme="mix" xml:lang="en"><term>handwriting recognition</term>
<term>neural networks</term>
<term>postal automation</term>
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<front><div type="abstract" xml:lang="en">In this paper, we present a system towards Indian postal automation based on pin-code and city name information. In the proposed system, at first, non-text blocks (postal stamp, postal seal etc.) are detected and destination address block (DAB) is identified from the postal document. Next, lines and words of the DAB are segmented. Since India is a multi-lingual and multi-script country that was earlier colonized by UK, the address part may be written by combination of two scripts: Latin (English) and a local (state) script. Here we shall consider Bangla script (local state language) with English for recognition. It is very difficult to identify the script by which the pin-code portion is written. So we have used two-stage artificial neural network based general classifiers for the recognition of pin-code digits written in English/Bangla. To identify the script by which a word/city name is written, we propose a water reservoir based technique. Based on script identification result the city names on the corresponding script will be recognized. For recognition of city names we propose a NSHP-HMM (Non-Symmetric Half Plane-Hidden Markov Model) based technique. At present, the accuracy of the digit recognition module is 93.14% while that of city name recognition scheme is about 86.44%.</div>
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A System for Indian Postal Automation

A System for Indian Postal Automation

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