A New Approach for Arabic Handwritten Postal Addresses Recognition
This work addresses the domain-specific challenge of automating postal address recognition for Arabic handwriting, which is incremental as it applies existing methods to a new dataset.
The paper tackles the problem of recognizing Arabic handwritten postal addresses by proposing an automatic analysis system using the beta elliptical model and graph-matching, achieving a recognition rate of about 98% on Tunisian postal envelope data.
In this paper, we propose an automatic analysis system for the Arabic handwriting postal addresses recognition, by using the beta elliptical model. Our system is divided into different steps: analysis, pre-processing and classification. The first operation is the filtering of image. In the second, we remove the border print, stamps and graphics. After locating the address on the envelope, the address segmentation allows the extraction of postal code and city name separately. The pre-processing system and the modeling approach are based on two basic steps. The first step is the extraction of the temporal order in the image of the handwritten trajectory. The second step is based on the use of Beta-Elliptical model for the representation of handwritten script. The recognition system is based on Graph-matching algorithm. Our modeling and recognition approaches were validated by using the postal code and city names extracted from the Tunisian postal envelopes data. The recognition rate obtained is about 98%.