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Classification and recognition of handwritten digits by using mathematical morphology

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Abstract

The present paper proposes a novel algorithm for recognition of handwritten digits. For this, the present paper classified the digits into two groups: one group consists of blobs with/without stems and the other digits with stems only. The blobs are identified based on a new concept called morphological region filling methods. This eliminates the problem of finding the size of blobs and their structuring elements. The digits with blobs and stems are identified by a new concept called ‘connected component’. This method completely eliminates the complex process of recognition of horizontal or vertical lines and the property called ‘concavities’. The digits with only stems are recognized, by extending stems into blobs by using connected component approach of morphology. The present method has been applied and tested with various handwritten digits from modified NIST (National Institute of Standards and Technology) handwritten digit database (MNIST), and the success rate has been given. The present method is also compared with various existing methods.

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Authors and Affiliations

  1. Department of Computer Science and Engineering and Information Technology, Godavari Institute of Engineering and Technology, Rajahmundary, 533 296, India

    V. Vijaya Kumar

  2. Department of Computer Science and Engineering and Information Technology, Rayapati Venkata Ranga Rao (RVR) and Jagarlamudi Chandramouli (JC) College of Engineering, Guntur, 522 109, India

    A. Srikrishna & B. Raveendra Babu

  3. Department of Computer Science and Engineering, Godavari Institute of Engineering and Technology, Rajahmundary, 533 296, India

    M. Radhika Mani

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  1. V. Vijaya Kumar
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  2. A. Srikrishna
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  3. B. Raveendra Babu
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  4. M. Radhika Mani
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Correspondence to V. Vijaya Kumar.

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Vijaya Kumar, V., Srikrishna, A., Raveendra Babu, B. et al. Classification and recognition of handwritten digits by using mathematical morphology. Sadhana 35, 419–426 (2010). https://doi.org/10.1007/s12046-010-0031-z

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  • DOI: https://doi.org/10.1007/s12046-010-0031-z

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