Title: Automatic extraction, segmentation and recognition of multi-font Indian Pincode

Authors: R. Radha; R.R. Aparna

Addresses: S.D.N.B. Vaishnav College for Women, AFF Madras University, Shanthi Nagar, Chrompet, Chennai, Tamil Nadu – 600044, India ' S.D.N.B. Vaishnav College for Women, AFF Madras University, Shanthi Nagar, Chrompet, Chennai, Tamil Nadu – 600044, India

Abstract: This paper proposes a new algorithm for Pincode script identification (PSI) that would detect Pincode in the address image of the envelope. The developed system differentiates the scripts of English alphabets and numerals. A new method for normalisation of extracted chain code features is proposed. The extracted numerals of various font types (multi-font) were recognised using multi layer perceptron (MLP) with back propagation (BP) algorithm and Naive Bayes classifier (NBC). The recognised Pincode was used for automating the sorting process. The experimental results of recognition of isolated Pincode were discussed. Recognition accuracy of 95% for MLP-BP and 93.8% for NBC was obtained. The performance comparison of MLP-BP and NBC are discussed in this paper.

Keywords: neural networks; segmentation; binarisation; bounding box; chain code; back propagation; naive Bayes classifier; India; Pincode script identification; address images; feature extraction; address recognition.

DOI: 10.1504/IJCVR.2014.062953

International Journal of Computational Vision and Robotics, 2014 Vol.4 No.3, pp.247 - 258

Received: 22 Jul 2013
Accepted: 02 Nov 2013

Published online: 25 Jun 2014 *

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