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Bangla Handwritten City Name Recognition Using Gradient-Based Feature

  • Shilpi BaruaEmail author
  • Samir Malakar
  • Showmik Bhowmik
  • Ram Sarkar
  • Mita Nasipuri
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 515)

Abstract

In recent times, holistic word recognition has achieved enormous attention from the researchers due to its segmentation-free approach. In the present work, a holistic word recognition method is presented for the recognition of handwritten city names in Bangla script. At first, each word image is hypothetically segmented into equal number of grids. Then gradient-based features, inspired by Histogram of Oriented Gradients (HOG) feature descriptor, are extracted from each of the grids. For the selection of suitable classifier, five well-known classifiers are compared in terms of their recognition accuracies and finally the classifier Sequential Minimal Optimization (SMO) is chosen. The system has achieved 90.65% accuracy on 10,000 samples comprising of 20 most popular city names of West Bengal, a state of India.

Keywords

Gradient-based feature Handwritten word recognition Holistic approach Bangla script 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  • Shilpi Barua
    • 1
    Email author
  • Samir Malakar
    • 2
  • Showmik Bhowmik
    • 1
  • Ram Sarkar
    • 1
  • Mita Nasipuri
    • 1
  1. 1.Jadavpur UniversityKolkataIndia
  2. 2.MCKV Institute of EngineeringHowrahIndia

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