Bangladeshi Post Office Automation System Using Neural Network

Abstract

In this paper, bangla handwritten digit recognition based post office automation system has been proposed for Bangladeshi Post offices. Actually, postal automation is not any new concept in developed countries, as they are already practicing this. Though Bangladesh has entered in the digital era, postal systems are not digitalized still now. Proposed system automatically sorts mails according to the post code, thus it can save time and money, reducing the necessity of manual sorting. Envelopes of each mails are scanned and region containing post code information is segmented. Different positional and statistical features including Gray Level Co occurances Matrix (GLCM), Local Binary Pattern (LBP), Histogram of oriented gradients (HOG) feature based bangla handwritten digit recognition system is applied to extract each digit. According to post code, mails are stored in postal zone specific buskets. For recognising purpose, Multi Layer Neural Network is applied. Proposed system gains higher accuracy of 99.71%, thus it outperforms state-of-the-art methods.