A System for Indian Postal Automation
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Recognition of Numeric Postal Codes from Multi-script Postal Address Blocks
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
High performance classifiers combination for handwritten digit recognition
ICAPR'05 Proceedings of the Third international conference on Advances in Pattern Recognition - Volume Part I
Handwriting Recognition in Indian Regional Scripts: A Survey of Offline Techniques
ACM Transactions on Asian Language Information Processing (TALIP)
Proceeding of the workshop on Document Analysis and Recognition
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In this paper, we present a system towards Indian postal automation. In the proposed system, at first, using Run Length Smoothing Algorithm (RLSA), we decompose the image into blocks. Based on the black pixel density and number of components inside a block, non-text block (postal stamp, postal seal etc.) are detected. Using positional information, the destination address block (DAB) is identified from text block. Next, pin-code box from the DAB is detected and numerals from the pin-code box are extracted. Since India is a multi-lingual and multi-script country, the address part may be written by combination of two languages: Arabic and a local language. For the sorting of postal documents written in Arabic and a local language Bangla, a two-stage MLP based classifier is employed to recognise Bangla and Arabic numerals. At present, the accuracy of the handwritten numeral recognition module is 92.10%.