A New Approach for Arabic Handwritten Postal Addresses Recognition

TL;DR

This paper introduces an automatic system for recognizing Arabic handwritten postal addresses using a beta elliptical model, achieving a recognition rate of about 98% on Tunisian postal data.

Contribution

It presents a novel approach combining image filtering, segmentation, and a beta elliptical model for improved Arabic handwriting recognition in postal addresses.

Findings

Recognition rate of about 98% on Tunisian postal data

Effective segmentation of postal code and city name

Successful application of the beta elliptical model for handwriting recognition

Abstract

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%.